Reflection & Proposal In our last lesson I ran through the initial stages of my final proposal. With assistance from my classmates and tutor I managed to finalise a problem statement and the direction for my final project. I got positive feedback regarding my area of interest and have thus begun thinking about how to visualise the project. My issue is centred on promoting the voices of people in offshore detention, emphasising their narratives using original content from social media platforms and in turn, enforcing a sense of connection and tangibility to these narratives. To maintain a focus on the stories of people in offshore immigration centres, the piece will focus on language, in particular through unadulterated and self-directed refugee stories. I will contrast these stories with mainstream media narratives and official statements given by the Australian government. This lends itself to a generative printed project resolved using typographic detailing. It was suggested that I might want to use older projects from last year to influence my resolve, for example the book TL;DR. Using this idea of a publication design, I’ve furthered the resolve into a newspaper format, reinforcing notions of the media and how it influences public perception.
Revised Proposal
Project title: Voices in Manus
Practice type: Poetic Generative Data
Problem Statement:
Since the early 2000s, the Australian government and the media have politicised refugees and asylum seeker issues. Our government and legal system have engendered a societal complacency on these issues, through the introduction of mandatory offshore processing, an effective media blackout within the detention centres, and other measures that place the plight of refugees outside of the public spotlight. Our media, often depicting asylum seekers as ‘swarms’ and ‘masses’, has successfully alienated their experience from Australian society, to the point where the majority of Australians believe that they are unworthy of our help. If racist attitudes towards those seeking asylum aren’t challenged, these attitudes will continue to proliferate and become further normalised amongst a larger proportion of the community.
Possible change: In my project I hope to shift public perception and attitudes towards refugee and asylum seekers by focusing on refugees’ subjectivity, recognising and acknowledging the sense of identity that has been robbed from them. To achieve this I will be exploring ways to visualise and compare the stories of people in offshore immigration detention with official statements and comments from prominent members of the Australian government, who have shaped this issue in the past few decades. The resolve will be in the form of a publication design. I will be exploring how to visualise key messages through various typographic techniques, and a range of materials. The power in this project lies in creating a sense of tangibility to the experiences of refugees, who are too often overlooked and sidelined. It therefore aims engage an audience that might otherwise be disinterested or disengaged from the issue.
Image Reference:
Wallman, S, A Guard’s Tale (2014)
Before the discussion on my proposal that I had with my peer Liz, I was already a little unsure of what I was creating, or what my actual outcome was to be. Through further research before the session, I had discovered or rather specified exactly what was my specific issue dealing with 18-25 year olds, and what I wasn’t the outcome to do.
It was clear through research that the monitoring and data collection wasn’t going to end or let up any time soon, especially not with the inclusion of the Internet of Things. And so rather than designing a possibility to end the monitoring on wither end, it was decided that my proposal was aiming at creating awareness of the increased privacy issues, and get round adults to spread the word or understand the Internet of Things. Thus, my proposal was to create awareness, to educate, or to inform.
I didn’t exactly have an actual proposal idea to run through with my peer in the class session. I had a few ideas floating around that I had picked out from the brainstorming session around the 5 possibilities to create change, however I wasn’t sold on a particular one. And so, in the session with Liz, I decided to quickly run through my 5 ideas–quite briefly–and figure out if a particular one caught her eye.
None really did, or they weren’t at a point to yet.
However she was quite startled and intrigued by a story I told her that I founding a news article. Basically, the gist of the story was that a young woman had extremely private and intimate personal data collected from a product of hers, when she had no idea she was being monitored. This snippet sparked both our interests, as it really portrayed the idea that public entities such as business and companies can collected very private data from us without our knowledge, in very private settings and environments. Who knew that you could be monitored through products in your house or bedroom.
Even thought I didn’t have an exact proposal, she did give me some advice and feedback on the ones that I did have, and brainstormed other ideas with me.
The first piece of information the she gave me was that she like the idea of creating awareness or informing the generation of the lack of privacy. We both felt that the monitoring wasn’t going to stop, and luckily she agreed with me. And so this now became the focus of what I wanted my system or design to do ultimately.
Due to the short story that I had told her, and the fact that she was quite shocked by the invasive nature, she felt that it could be a good idea to focus on a specific set of data to help ground the proposal or make it more emotional. While being specific like personal details could have worked, she suggested that I look into creating a proposal around the really private data that we have, such as in the story told. This notion also helped to develop my proposal as there are lots of ways that we give out private data, however most of the time we know we are giving it out. So I thought it could b interesting to focus on the times that we are unaware that we are providing private and personal data, such as in the Internet of Things.
Another piece of information or critique that Liz provided to me was to place whatever my issue or proposal was, into a real world content. Place it in an area, a time, a place, a social setting. And that way, whatever my proposal ends up to be, it will be relatable to the generation or audience the tis it being designed for. Immediately, this made me think of social media and anything online, and also of the bedroom. People always say, or at least imply, that our bedrooms are a visual expression of who we are; our interests, loves, personalities etc. So why not place my proposal in the context of the bedroom and online. There isn’t one person that I don’t know that doesn’t use their phone at least once a day in their bedroom, or doesn’t use a single piece of technology or a product daily. If I had to look around my room, I would at least see a computer, a laptop, an iPad, iPod, phone, Nintendo 3DS, Wacom tablet etc. So it’s fair to say that this setting could work effectively for my target audience.
The final piece of information that we discussed was another port of WHY? Why was I wanting to create something like this? Why were they to interact with it? Why was I thinking of a service design over any of the other emergent practices? The gist of our conversation was that I want people to care. Care about their privacy, care about what information they are putting out there, and care about who is viewing it. So along with the basis of informing the audience or making them aware of the Internet of Things, I really wanted to find a way to make them care.
This session was very helpful as I was able to get another brain on my issue. I could work out if things were working and whether I was in a correct direction, or if I had completely lost the plot. It also taught me (again!) that everybody thinks differently. What I figure could be an excellent idea, could be terrible for someone else or vice versa. I understand exactly now why there is usually user testing and prototyping along the way for all projects.
So now for my revised proposal—
Growing up in the age of Technology, 18-25 year olds have witnessed the rise of the Internet and its wide spread use. And in todays society we are being introduced to the Internet of Things, a system where all devices and products will have the ability to connect to the Internet and feed information to their suppliers and companies. However, users this age aren’t aware of the Internet of Things or its increased invasion of privacy. While they don’t necessarily care about their online privacy, they know what personal information should or shouldn’t be posted. The problem becomes the increased invasion of data monitoring with which we are unaware of in public and private spaces.
Since the internet is so ingrained in our daily lives, ending the data collection and monitoring isn’t a possibility. Instead, the change would be to create awareness and inform this generation of the increased potential for data monitoring with the inclusion of the Internet of Things. The change should get them to think differently about the Internet of Things and what products could be linked and connected, as well as how they interact with their private and personal environments. The change should start a conversation between this generation, for them to continue to spread the word.
Which brings me to my possible design action. The Unseen, or Unseen Connections (the name is pending), is a service design that aims to create change. The proposal is an augmented reality app that shows or reveals the unseen connections that products and devices have to the Internet of Things. The user could be introduced to the app through a social media hashtag that sets up the campaign and encourages them to see their ‘home’s Internet of Things’. After answering a few questions, and inputing parameters for daily use, the app then accesses the phones camera and superimposes graphics and lines over the real life image. The app reveals what devices are or could be connected, revealing to the user the possibility for data monitoring and collection. After this, the app also provides tips of ensuring your privacy in the Internet of Things, especially your bedroom, based on the results seen in the camera. From here, the user is then encouraged to continue the conversation, and spread a link or the hashtag to their friends and peers on social media. Reveal the connections, be informed or shocked, and spread the word.
The image above depicts the brainstorming session that our group had around my issue. It was decided early on, that having individual pages for each issue would invite us to throw any and all ideas on the page, and encourage us to fill the space with possibilities.
Another rule for the group initiated early in the process was that there was to be no judgement with regards to the ideas conveyed. This ensured that it was quantity being created rather than quality (a particularly strange concept to wrap your brain around when the whole course has been about the quality of work and concept).
With these rules in mind, we began to brainstorm each others problem statements individually. Spending around 15 minutes on each person, we spoke about the possibility we were imagining, and then wrote them down. Often times one idea would spark another, and branches of ideas similar to each other would be created.
What I found good and useful about this process of brainstorming was that I managed to get different perspectives on my problem and issue, and provide ideas from an outside point of view. For the past 7 weeks I have mostly been the only one researching and developing my issue, so to have people brainstorm visual responses as if they were possible users, was a great and useful experience. The process also allowed for undiscovered concepts and visuals to come to light. There were some ideas mentioned that I hadn’t thought about, and managed to spur different thoughts.
However, there were some down sides to this brainstorming process also. The main disadvantage was that the problem statement that I had wasn’t well researched and I didn’t have a sufficient understanding of the issue, this was because it was spurred from a comment of one of my peers. It would have been better to originally choose the internet f things like I had been researching, to get actual concepts and possible responses I could have developed. The other slight issue that I discovered with this process was that my peers did’t have a great understanding of the issue as well. It way have just been that I didn’t explain certain parts of it correctly or well enough, but seeing as data issues generally aren’t talked about, it was hard to brainstorm solutions.
Overall, the process was helpful in providing more eyes to bounce ideas off and see what they would do in my situation, however it would have been more effective if I had chosen a more researched (and possibly broader) topic in order to get ideas to develop.
After the slight disaster of my part of the group brainstorming session, I decided to do further research and try the exercise again. Since the Internet of Things was a focus for the past few weeks, I decided to create another problem statement, but with privacy and the Internet of Things as the centre of the exercise.
New problem statements
With the map above, I felt like I had a better idea of my concept and problem, and could create more possibilities for change. Or at least there were more opportunities to look at. And so, with the top right map being a little tight, I recreated it on a larger page, and kept developing visual responses and ideas.
New possibilities of change
While it was great to redo the class and group exercise of brainstorming the possibilities for change, doing it by myself lacked the group experience and the opportunities created by having multiple eyes on the issue. The next step would be to get another person to briefly look at the ideas presented, and see if they can add some, or change any that are existing.
After weeks of researching, it now came time to start thinking about the end game. What can I turn all of this research into, and what kind of design response could be created?
The individual and collaborative tasks that were undertaken in class were very helpful–if only I had a good grasp on a specific data issue! The first section of the exercise was to individually develop a problem statement. Throughout the research process, I hadn’t investigated a specific issue within data privacy and surveillance. And although the Internet of Things was somewhat specific, at the time of the problem statement it didn’t feel specific enough. So with a brief discussion of issues and topics with a peer, the issue of patient data came to mind as a specific concept that was also present in the research. With this brief topic in mind, I tried to develop a problem statement.
Initial problem statements
However, it almost seemed too specific (topic / user wise), and was probably too long. Shortened, it came down to patients wanting control over their heath data. It was almost too specific because there wasn’t a lot of room for interpretation or response development because the topic was too small in terms of who it involved and creative solutions. I almost needed something more varied and broad that could also be specified in certain situations.
But I powered on with the specific patient data, and used the problem in the next stage of the task which was to brainstorm any and all visual design responses to the problem statement that were of an emergent practice. This was difficult as not only did I not have a lot of understanding of the problem and key characteristics, but there was nothing to clearly explain the problem to my peers.
Even still, we brainstormed for around ten minutes and came up with few possibilities. Not nearly enough to develop a good proposal for though.
Group brainstorm of possibilities of change
After taking a week off the research and development, I wanted to ty the exercises again. So after doing some more secondary research, and going back to my original topic of the Internet of Things, I developed new problem statements, and brainstormed new possibilities for visual design responses.
Initial problem statementsInitial problem statements
It was decided that the responses would be around education, warning and limiting the problem rather than stopping it, as the data privacy controversy won’t end any time soon while the Internet of Things is active and growing.
Five ideas stood out as the most possible and interesting, as well as the best responses to the problem.
While the emergent practices were in the foreground of my mind, I feel that some of the responses may need a greater connection to one of them.
A data visualisation on the places that you would get targeted / monitored, or what types of data would be collected if a particular suburb or local area were to be a smart city in the Internet of Things.
A new service / policy for companies, governments and businesses to comply to. Like Microsoft’s DNT.
An opt-in / opt-out system / service that could act as a way to be a part of the data collection and monitoring as little or great as you want (limits).
A data visualisation on how much of ‘YOU’ can be collected through the Internet of Things data collection / monitoring.
A service that aims to spread the awareness of the Internet of Things around the home, especially with regards to public entities monitoring your private data without you knowing about it.
I tried to keep the same mindset of the process taken in the original brainstorm session in class: there is no judgement, the aim is quantity over quality, and it shouldn’t be too hard (in terms of how the concept can progress or be adopted. It would have been good to have another person to bounce ideas, however the time frame left me short.
From here, it was time to determine a particular response that fitted best into one of the emergent practices, and had the most possibilities for change. It came to my attention that the solution was not going to be to stop the monitoring or end the tracking of private data as it is already too prevalent in today’s society. What is needed, is a way to create limits on the collection and monitoring of data, so that the users are given part of the control. Or at least there could be a compromise.
One possibility seemed the most interesting and direct in creating an intervention: number 3, an opt-in / opt-out system / service that could act as a way to be a part of the data collection and monitoring as little or great as you want (creating limits). Being in the so called technological age or generation, 18-25 year olds have grown up with technology and the internet. They have seen it been born and grow into a gigantic virtual world that is used daily. However, with all of this growth and use, some things have been lost. With the terms and conditions of online websites being so long and in such fine print, they are generally skipped over and forgotten about. Or on the other hand, the terms and conditions are deliberately placed in hard to find areas on sites. What is needed here is a system that is in the control of the user. And so, this proposal aims to give control back to the user by creating an opt-in / opt-out service. For every site (or connected product / place in the internet of things), users could be presented with a short form, or a button that transforms into a slightly longer form. The concept is, that through a standardized form or set of questions, the user could state how much or how little or particular things they would want to be tracked. This way, instead of just stating ‘track’ or ‘don’t track’, they can be involved in some aspects, none at all, or only for particular companies / products they trust. There is also potential for the system to go further and block particular details of the user, so their online persona turns into a bunch of statistics rather than a digital personality. The tracking and monitoring control would be up to the user.
While this could be a solid idea, it is only a draft at this point and could (or most likely would) change in the near future.
This mind map looks at areas of interest to address within my problem statement. The map is divided into two broad issues, to help narrow down my focus. While the issue of national security was intriguing to me, I ultimately decided to focus on ownership of information as it was a much more universal issue. I made this map before generating problem statements to help summarise my view of the topic, and ensure that my statements were relevant to the issues I wanted to pursue.
This less well organised map shows some of the problem statements I generated before choosing and refining. In generating problem statements I tried to be as specific in situating the issue; which was difficult to do while keeping the phrasing succinct. Moreover, I was also careful to not make the statement so specific that I would have trouble generating design proposals in response to it. The statement I chose to refine from this exercise was “users are disconnected from the information they provide to online services”, which was later modified to “users are disconnected from the personal information they provide, either willingly, or unwillingly, to online services”. Adding in the phrase about willingly or unwillingly providing data addresses not only data collection programs, but also the data we agree to exchange when we register for online services.
Finally, this brainstorm looks at possible design solutions in response to my problem statement. Created in collaboration, with Brain, Chloe and Collette, this map encompasses both solutions, and broader ideas about what the proposal should accomplish. Despite choosing a relatively open statement, it was still very challenging to generate ideas. This is something that I think disproportionately affected the online privacy groups, as it is an extremely technical topic. Instead of focusing on mind mapping stakeholders and their emotions over the past weeks it would have instead been useful to undertake secondary research on the topic. I think that we spent too much time going over the same information in class and missed out on an opportunity to gain an understanding of the extremely complex mechanisms behind data surveillance, which in turn has made it hard to propose design solutions.
Like every tutorial in this subject, mind mapping was again introduced as a way to structure ideas around a topic. For online privacy, data surveillance and data security this involved writing down the same things as the previous weeks, only this time with a different word in the middle of the page. As you can probably tell, I’m a bit tired of mind mapping and question if there is no other way to promote discussion? With that being said, this week’s exercise was much more defined than other weeks, with a clear objective to work towards. I felt that having a defined outcome helped structure conversation and led to more motivated discussions, as everyone knew what had to be done in the allotted time. Doing individual mind maps in a group setting was another more useful approach to brainstorming that I felt helped incorporate different viewpoints. Working on other student’s mind maps also highlighted the variety that exists within the topic and the different areas of exploration that everyone had chosen to pursue. Below is the outcome of these activities. Despite this I still feel like there should be more communication from tutors about how these brainstorming activities inform our design outcomes for the forthcoming assessment tasks.
Defining the problem statement
Who does the problem effect? Be specific.
My problem effects every person and organisation that uses networked technology. In most cases these stakeholders are confined to developed countries, although this will no doubt become a global problem as technology becomes more and more accessible.
What are the boundaries of the problem?
Companies and governments are able to operate invasive data retention schemes due to a lack of awareness and understanding from users. The technology used to capture and analyse data is so advanced that there is almost no way for a layman to understand how it operates and how it breeches their right to privacy. Deliberately complex end user license agreements only seek to magnify this problem.
When does the problem occur?
The problem occurs every time a user connects one of their devices to the internet. Once online, data is collected about their activities, whether they specifically agree to it or not.
Where does the problem occur?
The problem occurs on every computer, tablet and smartphone connected to the internet. Data is collected from these devices on a massive scale, largely unbeknownst to the user.
Why is this important?
The issue of online privacy is important as effects everyone who uses the internet. As more and more objects become networked, it will become all but impossible to avoid having information collected about you. Companies and Governments are unlikely to change their stance on these invasive practices unless there is a large scale push to introduce stricter regulations of how and when information can be collected. More needs to be done to raise awareness of online privacy and the ways in which companies collect and use data they collect from individuals.
Problem statement
Users are disconnected from the information they provide, either willingly or unwillingly to digital systems.
5 point summary
Create a data visualisation based on people’s online activities. The map would pinpoint locations where a user has connected to a network in order to show how detailed information can be extrapolated from seemingly innocuous data points.
Design a service that converts complicated, end user licensing agreements into plain text. Doing this would allow people to better understand what information they are granting companies access to when they agree to use a service.
Create a service to personify data inputs when registering for online services. By making the data entered more personal, users will be more cautious about what information they provide. An example of this is a map, instead of a text field for specifying address.
Design a data visualisation based on publicly accessible information, such as geotagged posts and photographs. Build up a map using this information to show how easy it is to access this data as a user, let alone as a company with access to powerful scraping tools.
Create a service which adds tracking cookies at outgoing data packets in order to allow users to see where their data is being sent. This would reveal the database it initially gets sent to, as well as who else it is shared with. This might not even be possible to design.
Proposal
To raise awareness of the amount of information user’s provide, either willingly, or unwillingly to online services, I plan to create a data visualisation based off publically accessible information. To do this I want to gain administrative access to the Visual communication and Emergent Practices blog to install a widget that records IP address. Tracking widgets like these are offered by WordPress as a means for bloggers to better understand their audience, but in this case would function as a very basic scraping tool. Although invasive, this IP widget possesses nowhere near the capabilities of programs run companies such as Google and Facebook. After collecting this information, I would then run reverse searches on all of the IP address to pinpoint the location of every student using the blog. Cross referencing this with other data, such as their WordPress username would allow me to paint a fairly detailed picture of every student’s name and geographic location. Doing this would not only show how easy it is to use data to create user profiles, but also highlight how powerful these major tech companies must be. After all if a single student with no coding experience could gather this much information, how much more must Google and Facebook know about me?
Twitter is a social networking media, which allows users to publish and share messages that are visible to other users. These messages should be limited in the 140 characters or less in twitter, uses can found lots of different users on twitter, which is include basic communication between friends and family, a way to publicise an thing, or companies use this tool to communicate with their clients. Twitter was founded in 2006, and was the third most popular social network media after Facebook and Myspace.
Data Pipeline is an embedded data processing engine for the Jave Virtual Machine. Users can use it to convert incoming data to a common format, prepare data, migrate between databases. replace batch jobs with real-time data. Data Pipeline is very easy and simple, uses can quickly learn and use.
I was typed my issue( refugees and asylum seekers) in Data Pipeline search, firstly, I received 500 tweets, then if need more data, you can chose search more than 500 tweets, also you can download tweets to excel, and you can choose emailed results to you daily.
In the issue mapping workshop, we’ve analysed and speculated around the issues, associations, stakeholders, human and non-human values within our issue of online privacy. What we found interesting was the vast spectrum of controversies around data security, online privacy, the social, economic & political factors of this broad concept. So the initial input we had was the categorise the main variables that contributed to the 3 focuses, and they were: Individuals, Internet and governments/ corporations/ organisations.
From here, we’ve focused on a particular aspect of online privacy, that being, governments and individuals and how they relate or differ. One interesting point that determines its changes is the presence of online activity. The idea of a global sensation being more open and vulnerable. Both individuals and corporations strive for property ownership which ultimately as a collation of data. It is driven by business and profit incentives. Social media as a platform for communication and exchange has contributed extensively to the social and economical factors of online privacy. For example, Google, Facebook, telecommunication services such as Telstra rely on the personal data and interactions of individuals to stimulate a global network.
Once we’ve acknowledged this complex network, we then delved into characteristics and features of our issues. Creating a data set of objects and words derived from the themes (see map above). We also looked into the paradoxes and controversies of online privacy and the emotions/ motivations that outline their objectives.
Understanding how individuals, the internet and the government/ organisation plays a critical role in this intricate network, It opens up possibilities and design orientated scenarios to approach for our design responses. I was really interested in looking into the relationship of digital technology and their association with data. In particular, I wanted to understand the role of a surveillance camera in a public/ private space and the interactivities with the general audience. This will inform my approach for the designed response.
The history and context of language are always changing and developing. As the emergence of technology and the Integration of the Internet changes the way we consume media. Our linguistics and vocabulary also expand. Social Media in its own platform is a major contributor in the ways we communicate visually and audibly. The format and structure of social media influences writing styles as well as content. Twitter is a new form of media that delivers its messages in a 140 character limit. This restriction creates a succinct, creative and empowering conversation that users are easily able to engage and scroll through.
Lexicons are a linguistic resource that we use to understand the vocabulary of a person in association to words of sentimental value (emotions). Whether they’re positive, negative or neutral. I.e. ‘NO!’ and ‘no’ conveys a different tone of voice and with the slight alterations in its composition, It delivers a different message. Twitter is a primary social media platform that deals with languages of informal expressions. Generally a collation of data and colloquial expressions. Such as acronyms, the use of incorrect spelling/ terms and abbreviations. Due to the vast majority of language expressions and variable factors, It is difficult to determine whether the responses are of sentimental value (positive, negative or neutral) therefore the use of emoticons are applied.
Emoticons are a highly recognised attribute to the Internet language. The use of visual expression displays a greater range of sentimental values and is a language technique globally practised. Emoticons are considered to be opinion lexicons and are stable for sentimental classification, unlike literal words.
The default Twitter search allows users to add emoticons to the search to find positive/ negative tweets. The majority of tweets does not contain emoticons which impact the search and statistics by DTA: 25th Australasian Database conference shows that only 9.40% of tweets in 2011 contain at least one emoticon. 7.37% of that is positive and 2.03% negative. (Mohammad, S, A. Wang, H. 2014). Due to these results, It shows a decline and insufficient use of lexicons and emoticon limitations.
Twitter features using # syntax as a mean of collating tweets into categories and as a new form of internet language. Hashtags are also a form of metadata by collecting words of the same topic giving context to the tweet. For example #idontwanttowritethisblogpostanymore groups tweets with similar concepts. Although topics that are not typical are often more difficult to evaluate and contribute to the global expansion of lexicons, providing better performance to searches and collation of material.
Social media is a large and prevalent force within society. There are various social media platforms that people can use to obtain and share information on current issues in society. They are a simple way for people to interact and communicate their opinions and beliefs with each other on certain issues in the world. Social media is extremely powerful as it can be an agent for change and can heighten awareness on particular concerns in society.
Twitter
For this research, I have used Twitter to gain further insight into the perspectives of mental health in Australia. Twitter enables registered users on various devices to send, read and share short messages limited to 140-characters. It is a free online social networking service that many people use to share their opinions on issues and receive information on particular topics. Tweets can be commented on, liked or retweeted and contain conversation threads, hashtags to connect to general topics, hyperlinks to relevant websites and tags to other users. Twitter is a public service so users can follow/ be followed by anyone and tweets are permanent and searchable.
Data Scraping Process
The process I used to collect data was the Twitter Archiver add-on in Google Spread Sheet. Once I had connected my Twitter account to my spread sheet, I created a rule to find tweets catered towards my issue. It took me a few attempts to achieve a good set of data. My more specific searches didn’t bring up any tweets so I first searched broadly using the hashtag #mentalhealth in Australia and in my second search I specified the words stigma, mental and health. This brought up lots of results from many different stakeholders. From here, I went back and forth between the spread sheet and exploring Twitter manually for tweets. Using the spread sheet and Twitter directly, I found this method of data collection quite beneficial and discovered more information about mental health.
A rough flow chart of my data scraping process.
First search rule.
First data spread sheet.
Second rule.
Second data spread sheet.
Outcome of my data scraping
Below are some tweets that stood out to me in my data collection and analysis:
A common hashtag within the topic of mental health was #ImEndingStigmaBy which demonstrated the positive attitude towards the issue on social media.An example of how a hashtag can manifest in reality to spread awareness and knowledge of mental health issues.This tweet is linked to my specific topic of stigma in relation to communication between health professionals and patients.This tweet demonstrates the frustration of stigma felt by people and how there is a drive and determination to end stigma and discrimination.A stereotype of stigma and mental health is that there is only focus and awareness on particular illnesses such as depression and anxiety.
Reading through all these tweets from my data spread sheet made me realise that the view of mental health on Twitter is extremely positive. Having researched mental health continually for the past six weeks, it’s hard to see the positive side of the issue. Negativity and stigma are prevalent forces within the issues of mental health but I was pleasantly surprised to see the positivity and support displayed in these tweets. They mostly speak of increasing awareness of mental health issues, boosting positivity and helping spread the word for particular mental health illnesses and campaigns. This data demonstrates the power that social media has today in increasing awareness for particular issues.
Various stakeholders can also be identified through this data. Stakeholders on Twitter vary from people suffering and/or affected by mental health problems, bloggers about mental health and wellbeing, doctors and health professionals and also organisations such as SANE Australia. A lot of opinionated data can be collected from these individual profiles to gain a greater insight into the issues of mental health and how these stakeholders play a part within the issue.
Through my analysis of my data and further research, I have also identified some main hashtags used in relation to mental health which I have categorised into a mind-map (yes, another mind-map) below. Main hashtags that I discovered included:
#mentalhealth
#stopthestigma
#stigma
#depression
#anxiety
#wellbeing
#mindfulness
Other hashtags that were quite prevalent in my searches include:
#ImEndingStigmaBy
#22pushupchallenge
#imnotashamed.
#EndTheStigma
#SickNotWeak
Main hashtags related to mental health colour coded into positive, neutral and negative.
Hashtags demonstrate what is trending and provides an overview of particular topic, in this case, mental health. Again, it is interesting and enlightening to see that most of the hashtags used are positive and forward thinking.
After wading through all that data, I have created a five point summary about my experience of data scrapping and my view of Twitter:
Positivity stood out amongst the negativity.
Hashtags are annoying, yet helpful for data purposes.
Social media has a great power to boost awareness of issues.
Opinionated data offers a greater insight into various issues.
Use Twitter wisely; anyone can see it.
Visual Design Responses
It is still hard to say at this stage what design responses I could use to visualise this data as the information I have collected is still quite broad and abundant. A possible visual design response for this data on the issues within mental health could manifest as an interactive installation outlining the stakeholders involved and emotions experiences. I believe emotions and empathy is a key factor in understanding mental health issues. An engaging design like an installation would make the issue real to the audience. I would also like to explore the disconnect experienced when articulating ones mental state and how this can be perceived as attention seeking. Again, I could use emotions and feelings experienced by people to perhaps create a generative design response.
Co-creation has always been a slightly terrifying concept. However, it is also sometimes a relief. This post will explore my experience with co-creation in mapping controversies and actor profiles, in the data privacy sector.
The first task to work through was yet another mapping exercise around data privacy and its stakeholders. Except this time, in pairs. While this was an easy enough task to complete, both of us had slightly different understandings of what we were to do. With our previous individual and group maps by our sides, my partner was just recreating it with the same stakeholders, while I was trying to be more specific. Who exactly interacts with data and online privacy, and what specific parties are affected by all its facets. Part of this process was helpful as it provided me with a different perspective on the issue and those involved, but the other part of it was also difficult as no two people think alike, so instructions got lost in the mix.
Remapping the stakeholders
The next task was to map the controversies surrounding the topic of data and privacy. This task was a better use of the co-creation as it really explored many different facets of the topic. While my research was looking into ownership and the internet of things, my partner’s research was delving into personal data, especially with regards to mobile applications. Therefore, many different specific issues were being covered, and the controversies–or polemic–map could be all inclusive. What worked the best here was just writing it down on the paper. What do they feel? What do they feel that way? What would the opposite side of this polemic feel and why? A confirmation that is was relevant to the topic was often stated, however the process just called for as many controversies as were possible. This ‘no-judgement’ policy was accepted throughout the tasks.
Polemic map
Following the polemic map, the co-creation took on a more hands-on approach with the mapping of a particular polemic. ‘Ownership’ was the chosen polemic, as it had more possibilities in terms of where it lied in context, and who it affected. This stage of the co-creation workshop proved to be a little difficult. It was excellent to have another person’s ideas and train of thought, however, like earlier, we had slightly different notions on what was to be mapped. A conclusion was made here that even though it was a ‘co-creation’ task, someone needed to take the lead to keep the thoughts flowing, and pens moving. So while I took charge over the task, the ‘no-judgement’ policy was still in effect. However, the process of mapping the stakeholders, emotions and motivations to a specific polemic assisted in the development of a facet of data privacy. In other words, it helped develop an understanding of a specific situation.
‘Ownership’ polemic map
The next stage brought in another couple, building the co-creation group. While this initially seemed like a worse outcome giving the slight problems of just being in a couple, it actually proved to be easier. The conclusion early on was that the more hands (or brains) the more possibilities that can be created. And in terms of the task itself, it was enlightening to think of all the actors that play a role, or are affected in the data privacy sphere. Selecting the polemic of ‘ownership’, the task was to categorise all the actors present in the issue in terms of objects, emotions, representations, identities and other groups. What was interesting with this process was that it was thinking about the same human and non-human stakeholders, but going beyond what they are and looking at what they do. As Rogers, Sánchez-Querubín and Kil explore in ‘Issue Mapping for an Ageing Europe’, controversies should be taken as the starting point, and from there the focus is on the struggle, the action and the movement (p. 16). In other words, going beyond just what the stakeholders are, and looking at how they affect or are effected by particular polemics. It was also interesting to think of this map as a connection between human and non-human actors. As Rogers, Sánchez-Querubín and Kil pharaphrases Latour, ‘map not just human-to-human connections or object-to-object ones, but the zigzag from one to the other.’ (p.17). And that is where the interesting lies.
‘Ownership’ actors map
The following and final task further expands on the actors’ map, however more puts us (the researcher) in the shoes of an actor. The task: to choose an actor, and portray them through certain characteristics. Who do they associate with? What are they responsible for? Whose values do they align with? This exercise certainly put you in the shoes of the actor you choose, mine being the hacktivist group Anonymous. While I had some idea of who they were and what they did, having the platform of co-creation helped develop a good character for Anonymous, and discover things that generally wouldn’t have been common thought such as their feelings, communications and motivations. Below is the collection of all actors mapped out in our group.
Specific actors maps
The particular section on social mapping in the ‘Issue Mapping for an Ageing Europe’ reading also assisted in understanding this task. It was the paragraph about the two types of actors: the intermediator who is predictable and doesn’t transform anything, and the mediator, whose outcome is unpredictable and includes transformation, distortion or translations of meaning and elements. Such things as hardware can generally be called an intermediator, but change something about it, or alter its state, and it can become a mediator. This is known as an ‘action to create change’. In terms of data and privacy, as well as ownership, this action could be that further education is needed in to the issue. This could be in the form of a poster or flyer, or even an additional screen before application logins that explicitly asks whether you want to be tracked or not. It could be an opt-out form that allows you to no donate data you don’t want to. The action to create change could be as simple as a login screen or a blocking product, or as complicated as a system or service that acts as a data trust to protect your data that you ultimately create. The possibilities could be endless.
REFRENCES:
Rogers, R., Sánchez-Querubín, N. & Kil, A. 2015, Issue Mapping for an Ageing Europe, Amsterdam University Press, Amsterdam.
Following the completion of this class and mapping exercises, I wanted to go back and try some of these tasks again. Further along in the process, my focus in data and privacy was becoming a little clouded, so I used these tasks to bring myself back into focus. Below are image of those efforts.
Remapping the stakeholdersRemapping the stakeholdersRemapping the stakeholdersRemapping the stakeholders
Twitter is an interesting program and media. It is a global source that is accessible to anyone that has the internet or a mobile phone, and due to this it redefined the time span for news to be spread or broken. If you want to get a story broken, or spread news about a particular topic, Twitter is your best friend. You aren’t following your particular recipient? No problem. As long as you have an account you can opinion-ate or inform anyone’s eye off–even if it’s not amongst the popular topics of pop culture, technology, breaking news, or politics. Through its hashtags and trending topics, Twitter is easy to navigate, and files everything into neat little boxes–fitted with further hashtags acting as sub-topics.
But what makes Twitter unique? What steps it away from every other social media that keeps people connected and allows sharing? Twitter users are restricted to a 140-character limit in every post. This may sound easy to overcome, but not so much when trying to condense complex readings into a short sentence. Generally used to spread breaking news, natural or human disasters or popular issues, this restriction allows for the point to get across immediately. While keeping it concise means your attention is grabbed instantly, the challenge is shaping the post so that is still makes sense. There is nothing worse than a post with very important words, but nothing connecting them. But the tone of the post also contributes. Most of the posts on Twitter can fall into two categories: opinionated (and biased), or informative (and educated).
With all of this in mind, it was time to undertake the web scraping task. Originally, the Twitter Advanced search paired with the Twitter Archiver Add-on seemed like the ideal program or tool to use. Not only was this task needed, I wanted to use it for my benefit, and expand on my knowledge of the Internet of Things and data privacy in general. The process of scraping the data with the Twitter Advanced search and archiver were simple: the words ‘data’ and ‘ownership’ must be present, and ‘privacy’ was a keyword that could pop up. However, this didn’t turn up much, and it felt that the search was moving away from the original intended issue. A few posts back, the Internet of Things was the focus or specific issue within data that was being investigated. In trying to get back on track, more secondary research was conducted, as well as a repeat of previous class exercises. By doing this, I would hopefully get back onto an issue that was talked about more, and that I could possibly create some visual design responses for.
So here comes the tool Brand24: an online program that business can use to monitor what social media users are saying about their company, with the additional feature of being able to respond to them. With a new focus in mind, a new process was developed–heightened by the added features and functions of Brand24. The first step is for the tool to search the internet for any posts with the exact phrase ‘Internet of Things’, and the added keyword ‘privacy’. From here, the process is to only search through Twitter posts, and then play around with the keywords. Based on the results previously, some key words could be added in to narrow the outcomes further, or another way is to input excluded words to hopefully specify target users or situations. The next stage of this process is to play around with the added features of the influence slider and the emotion scale. The influence slider allows you to see which tweets or people held the most influence in the search in terms of visits, retweets, comments and likes, while the emotion scale allows you to accumulate positive, negative or the default neutral posts. These extra features could aid the process–as well as the type of results–as I could see whether the tool was accurate in its findings, and get to the point straight away on what were the most popular tweets surrounding the issue. The final stages of the process is to visit the top sites tweeted about to expand my understanding of the issue further, and to revisit the saved search often to view the developments.
Proposed process
Below is a flow chart that demonstrates the process that was actually taken in this web scraping task.
Actual process undertaken
The process itself along with the Brand24 tool proved to be a good combination. The detailed and generative process that was designed was enhanced through the features and added functions of the web scraper. The combination allowed me to explore within a topic that was both specific but also broad. I could begin with the broad spectrum such as the Internet of Things, and narrow it down by ‘privacy’ keywords. Also, having excluded keywords such as ‘business’, ‘company’ and ‘patient’ allowed the search to zero in on more generalised posts that were hopefully more targeted to the everyday social media user. It was interesting to see what posts were collated when these aspects weren’t included.
The parameters
This exclusion did work, however, I felt that the results were very informative and unemotional. Although this was a very common nature with all of the posts gathered. Furthermore, the influence slider was both an advantage and disadvantaged it turned out. It was an advantage because it could narrow down on the most popular tweets in the search, eliminating a lot of the retweets, however it was also a disadvantage, because as the slider was increased, two things happened: mostly all of the results were of about 5 original posts retweeted multiple times, or some of the less retweeted and original content was eliminated–ultimately, a loss.
Examples of results with a low influence valueExamples of results with a high influence value
As implied previously, a lot of the posts were just statements or the name of the article / document attached to the tweet. Or if they were of an opinion, they were direct retweets of the original opinion. This result became difficult as I was hoping to discover some original posts that game an opinion on the privacy issues. However, these were far too rare and possibly due to either the broader spectrum of data and privacy, or the platform of Twitter as its character limit restrictions. Overall, this facet was a little disappointing.
Examples of the expansive retweeting
In terms of the Brand24 tool, it seems to make the decision of whether the post is positive, negative, or neutral, however, it often gets it wrong. If there is a negatively associated word in a positive post, then it will only judge the post on that word. Or if there is a link in the post, it just generally puts it as a neutral post. The same outcomes occur if the post is a statement and not an opinion. Therefore, the tool gets it wrong a lot of the times, skewing the results because it possibly lacks the human decision-making element.
Negative tweet categorised as neutralPossibly positive tweet categorised as neutral
With these results in mind, there are a few visual design responses that could arise–however strictly initial concepts. Firstly, a response could be a set of posters or a service design that aims to educate and inform users of the lack of or hidden, privacy in the Internet of Things. Along the same line, the response could be a system or service in the IoT, such as an app that acts as a VPN. It could be a new login screen on social media apps to opt-out of the monitoring. Or another response could be a flyer that is in the boxes of new appliances and products to warn people of its connection to the internet or iCloud.
Since this post was so large in content, ideas and data, here are my findings–of the web scraping and the task altogether.
Twitter allows for short posts but this also restricts what a person can say, conveyed through the extensive retweeting occurring.
With such a broad, new and big topic such as the Internet of Things, most of the posts are informative, and rather statement-based.
It is best to search around for a web scraper or tool that works best for you as it could make the process easier.
Even though the process didn’t work the first time around, I kept trying and changing the parameters until I found something that was both interesting and collated reasonable results. Playing around with the parameters meant that different dynamics could be explored.
When working with data and web scrapers, the task doesn’t always go to plan. Computers don’t think like us humans; they don’t see the emotional side.
Since this semester start, collaboration are introduced into our design project process from week 2-week 5.In terms of collaboration, we consider team composition, communication, distribution, knowledge-sharing and co-ordination that help us build understanding of collaborative exercise. As a group, we were asked to collaboratively map the issue of online privacy, as well as continue brainstorming the ideas of stakeholders involved in our topic. The collaborative exercise start with work in pairs and turn to as a four people groups, we built connection with others and gain a lot of insightful thoughts from the peer’s perspective around online privacy issue.
In week 2, we first work on the brainstorming section, which are list all the possible stakeholders of online privacy around “shared values”, “public and private”, “ human and non-human” and “political and proximity”. As I mentioned in my previous post, these maps presented how specific stakeholders deal with online privacy, as well as the line drawn between their different positions. Thought from peers in my group are quite different with my position, its expand my understanding of data/ online privacy, especially on big data and Wihileaks.
Afterwards, we generated “word associations” in week 4 class, we again shared the ideas around online privacy. The exercise expand the findings of possibility of online privacy, from broth one side and opposite side. We come up with some unfamiliar words such as HDI – Human Data Interaction and DDOS, most of them are well-known, so most of people picked the worth. Besides, the recombination of individual words to sentences, quite fun and understandable; it showed me the alternative and optional thought from others and collaboration exercise to help me further develop the project (Image 1).
(Image 1: week 4 mapping)
In week 5, we are introduced into controversy mapping; a controversy is a disagreement, a typically prolonged, public, and heated debate. As in pairs, we start with the stakeholder map we generated in week 3, bring forward them to explore the specific relationship between each stakeholders, how they affect each other to deal with online privacy (Image 2).
(Image 2: week 5 controversy mapping)
On the other hand, we created a chart that reflect on the correspondingpoints between controversy, emotion and motivation. It help us found point in this network, put possible things into the space, and then we can draw out the creative change based on these maps. Then we worked on the specific controversy – data ownership, and come out with some different findings. For example, we have the emotion of “non-opinion” and opposite way “ over-powering”; teenagers are non-opinion based, because they think they don’t car who own the data; for data mining companies/adults, they feel they are over-powering, they don’t want their info to be used (Image 3.4).
At the last stage, we as a group four has completed the “Controversy Actors” surround Hierarchies, issues, associate, politics, values and capacities.Findings and thought provide me more alternative ideas and find way to shift this issue in many different ways (Image 5).
(Image 5: week 5 controversy mapping)
Reflection
Collaboration workshop withy groups and peers help us further understand the topic and identify what we missed within our research. Fortunately, four of us in our group are focus on different topic around online privacy such as “ownership of data”, “Wihileaks” and “commercial data use”. So the different opinions from the same issue opened our mind to look at “online privacy” from quite discriminating perspectives. For example, thought from my pattern in “data ownership” help me gained a deep understanding of who do you think they can own your data, how data has been collected or what’s people’s attitude (age: 18-25) with data ownership – most of them don’t care who’s using and who own it. Look into the 5 weeks research, mapping exercise, I’m currently work on “ online privacy issue happened in commercial web development”. As I mentioned before, we need draw a line that can balance the relationship between online commercial and user privacy. So combine this ideas with the insight/understanding from co-creating task, I start clarified my approach in both side of human and non-human :
What need to deal with:
commercial website use user’s personal information without the user’s consent (human)
collect personal information (non-human)
teenagers (18-25) doesn’t care where there information go and any… (human)
the education level of privacy
Possibilities for action to create change:
From human side: a creative idea to educating people around the issue.
From non-human side: A third party platform to visualise information and deal with specific point around the issue.
The things we explored are still broad; based on the starting point, I will further build a deep insight of my design project.
Co-creating controversy maps was a great way to quickly gain a broad understanding of the topic at hand. Interestingly, although both my partner and I had undertaken prior research on the subject we had both focused on very different areas of online privacy. The task of co-creating these visualisations helped identify nuances within our research and allowed us to come to a more holistic understanding of the topic. In addition to sharing knowledge, it was also interesting to get another student’s opinion on the divisive issue of online privacy. Discussing the advantages and disadvantages of online privacy was valuable as it allowed us to identify the variety of arguments that stakeholders have expressed about the issue. With that being said, the actual output of the mapping activity has not been particularly helpful to informing my design approach. Although I found it useful to discuss the issue of online privacy with another student, the maps we created are all but indecipherable. Based on my observation of other group’s maps, this is not a unique problem. I feel as though the way the controversy maps were introduced, coupled with limited time we had to complete them promoted a singular approach; write everything and anything you can about the topic as fast as possible. While this method did create large sprawling visualisations, it discounted a lot of the subtly and nuance that exists within complex problems. An example of this narrow focus is evident in our stakeholder map, which based on our tutor’s direction, focused on individual organisations. I feel a better, albeit more challenging approach would have been to look at broad categories of stakeholders. Doing this would have allowed us to better focus on their interests rather than on their identity, ultimately leading to a deeper understanding of the problem.
This map was generated from earlier stakeholder maps seen in post 3. Building on from that, it looks at the emotions behind each issue and the motivations behind the various stakeholders. Interestingly the word which came up the most was control; governments want control over their population, companies want control over their share price, and users want control of their data.
I found this mapping concept very confusing to wrap my head around and thus did not generate a good outcome. This mind map builds upon the previous exercise, and incorporates stakeholders into the equation in relation to the issue of national security. The main takeout from this activity was that the media is highly influential in people’s perception of state sponsored data surveillance.
This image looks at two actor mind maps we were able to work through. In this case, two actors vehemently opposed to the others actions. This visualisation highlights the motivations of each party, and how their different ideological views inform their actions in regards to online privacy, data surveillance and data security. It was also interesting to look at how they work around the restrictions placed upon them by their environment.
This map shows all the actors; human and non-human associated with the issue of online privacy. This visualisation was more useful than some of the other mind maps as it provided a detailed framework around which to dissect our topic. Of particular interest in this map is the idea that data collected from users is a commodity. This raises interesting questions about how data is used as a new form of currency in the information age.
Twitter is a popular social networking tool that allows users to send a short, mostly text-based message up to 140 characters long known as a ‘tweet’. These tweets are then published online and can be publicly viewed. Twitter users can post their own tweets, follow the tweets of other users or contribute to a wider online discussion based on a particular topic or event.
Twitter is fast personal communication. People can share personal insights on something with other people. Moreover, they can follow the celebrities and send feedback on any events such as a live television show. It is also commonly referred to as a short web log (blog). Social Media News Australia reported that Twitter becomes Australia’s most popular social media microblogging tool with approximately 2.8 million unique visitors in Australia and over 300 million users worldwide in the early of 2016.
My research process
My specific topic is the association between sedentary lifestyle and obesity. Therefore, I searched using keyword ‘Obesity’, ‘Fat’, ‘Sedentary’, and ‘Lifestyle’ at first.
Twitter Archiver Research 1 – #obesity #fat #sedentary #lifestyle
The data that came out on the list was exactly same as what I though about. However, as you can see the above screen shot, only one tweet showed since I used too specific keywords. I realized that I needed to use more general and suitable words to collect useful data.
Twitter Archiver Research 2 – #obesity #fat
This is the result by researching using keywords of ‘obesity’ and ‘fat’. I could receive lots of personal insights about obesity, but it was hard to find the information what I looked for because keyword was so broad to bring about specific data. Nevertheless, there were few results were related to my topic. After this, I searched using keywords ‘lifestyle’ and ‘office’ as well; however, it was not enough to gather useful data. Hence, I moved on Twitter search engine.
As you can see the above images, I typed three words ‘fat’, ‘sitting’, and ‘office’, which are more related to my topic. Many tweets came out, and they all indicated that sedentary work made them being fat. It shows that many people already recognize sedentary lifestyle is associated with obesity, but all tweets were their feelings about being fat like sad or anger. There were no any solutions or ideas for that issue.
While I scraped data via Twitter Archiver and Twitter search engine, I found how they were useful tool to discover information what I looked at using simple keywords. Twitter Archiver offered the list, which included the keywords I typed. It helped me to recognize what kinds of issues people share and discuss nowadays. Also, it provided wider knowledge that is related to obesity issue. Overall, I could have a look different personal insights and opinions about specific issues. It is really good to know them as a designer because we have responsibility to act for people needs and build the solutions to solve problems. Therefore, it is appropriate tool to scrape data to understand specific issue and personal insights.
Social media has become an integral part in the interaction of people. In a world is becoming dependent on the Internet as it is today, Twitter effectively brings people and community closer to their interests and is a great social-networking tool to update the information including daily conversations, information sharing, news critiques, and updates about an user’s life in real time without the need to read newspapers or watch television. It is also used by the very popular movie stars to connect with the audience and fans.
In order to gain a border understanding of mental health by using web scrapping data techniques such as Twitter archivers and Data Pipeline, I have documented different data sets to assist me with my research on my mental health issue. From Twitter achievers in google sheet with the hashtag #mentalhealth, the result is fetched over thousands tweets in the world and up to 500 tweets in Sydney including positive and negative tweets.
To fully understand the depth of this research, I took a closer look at mental health tweets on Twitter avandced search. I found these hashtags #mentalhealth #depression #anxiety #ChangingMinds were among the most popular hashtags related to mental health. These collected tweets contain content where the individual appears to be sincerely writing tweets about their depression and anxiety, yet some phrases may come up as negative, in the overall context, they may not actually carry a negative message. In the case of mental health tweets, they are sometimes raising awareness of the impact an illness has on people’s lives. Additionally, the imageries, quotes and linked websites are used to aim users who might be in need of psychological help. Because when a user searches a topic or a hashtag, they can be linked to a conversation with others who suffer the same difficulties and find a community that doesn’t seem to exist in the real community around them. This is especially helpfull way in the mental and behavioral health space, where not only individuals, but organizations, institutes, and departments are busy tweeting the most interesting news, positive advices and thoughts on treating and understanding mental illness
Five points summary of finding:
Twitter has been used to create outreach opportunities for those seeking help, providing information with hashtags that link to awareness and fundraising campaigns.
A social network efficiently connects those who suffer from mental illness
Raising awareness of the impact mental illness has on people’s lives.
Mental health issues are more common than you think.
Mental health conversations often go hand-in-hand with discussions about individuals mood, anxiety and substance abuse
For this exercise I decided to focus on Twitter in order to gather data about the the publics view on homelessness. Twitter, created in March 2006 by Jack Dorsey, Evan Williams, Biz Stone, and Noah Glass, is an online social networking service that enables users to send and read short 140-character messages called “tweets”. These tweets can be shared and viewed publicly or privately. Additionally users can also add hashtags that will reach a wider audience when users search that specific hashtag. Users can read and post tweets and access Twitter through the website interface, SMS or mobile device app. Other additional features have been added to enhance the users experience when it comes to text limitation. These features include the Twitter timeline, pinned Tweets, polls, mention Tweets, lists messages and cards as well as click to Tweets to extend the conversations.
Essentially Twitter is used to connect people of all ages with the same interests. It can be used as a social and professional platform where users voice their opinion, breaking news, raise awareness on social issues, business, educational tools, share their thoughts and feelings and experiences through photos or tweets.
flowchart
findings
At first I was very specific with my Twitter search which proved to not what I was expecting.
Twitter Search youth homeless social OR australia OR youth OR homeless OR smelly OR privacy OR people OR alone OR mental OR health OR depression lang:en. Most of the results had surprised me as it validated some points that I had about social exclusion.
A lot of the search consisted on LGBT related tweets confirming that there is a vast majority of youths around theworld that feel socially excluded and are homeless. Although these results were interesting, it wasn’t enough data, so I generated a new search. To continue my research I excluded LGBT to see what the results will show. Twitter Search
homeless social OR youth OR homeless OR smelly OR privacy OR people OR alone OR mental OR health -LBGT lang_en – This search interestingly enough showed reoccurring views regarding homelessness. One of which was related to the issue of refugee VS homeless citizens. Most of the tweets explored the problem that the country is facing choosing between the refugees and the homeless citizens.
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Other tweets had a political view which relates to the new agreement for the US to send $38 billion to Israel.
Dr. Craig Considine – @CraigCons US govt. sends $38,000,000,000 to the Israel govt, yet this morning I walked my 3 homeless people on the way to work. This makes no sense.
Twitter search homeless “hobo ” social OR australia OR youth OR homeless OR smelly OR privacy OR people OR hobo -LGBT lang:en
Finally, drawing upon the exercise in class, we emphasised on the word hobo and its connection with the word homelessness. To further explore my research I added the word hobo to my search. I wanted to investigate what hobo means and the assumptions and different views the public holds. To start off I searched the definition of ‘hobo’. It is defined as a homeless person; a tramp or vagrant. When narrowing down my search I kept the meaning in mind and compared tweets. Most tweets referred to their physical appearance, others made fun of homeless people, lacking empathy for the homeless community.
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Whereas fashion brands used the word as the title of a fashion object or reflected the the garments of a homeless person which in a way, mocks the homeless population, misleading and gives the word a new meaning in a way that society sees fit.
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design proposition
In the next couple of weeks I hope to not only raise awareness about homeless but also explore the desensitisation of societies perspective about homelessness. I will be creating a service design that enables the people of the public and the homeless community interact with each other to break the barriers and assumptions of society.
summary points
Twitter & twitter archiver is a great online tool to gather data and understand how a wider audience perceives a certain topic.
When researching data, sometimes the simpler the better. Specific phrases can be very limited and one must be open to explore other options which can lead to an improved result.
People’s views can be interpreted in different ways. Most of which are based on assumptions rather than facts.
Very few posts reflected peoples motivation to help the homeless community. Rather it’s all talk but no action. (Did not see any movements or protests for the homeless community).
People use the word hobo for their own benefits not knowing the true meaning behind it and lacking empathy towards the homeless community.
The social media source that I’ve chosen to explore in this web scraper is twitter. As I’m sure you will now know, Twitter is a platform that enables the user to read and post 140-character messages, photos and videos. In this format, Twitter amplifies the nature of 24/7 media. The reactionary nature of social media serves to speed up the cycle of reporting and opinions. Hash tags and trending subjects both reflect traditional media and generate organic content.
It’s is a platform that enables the user to read and post 140-character messages, photos and videos. Since its inception in 2006, Twitter has evolved into a platform that fosters political engagement and discussion from a grassroots level, giving a voice to ordinary people and breaking down traditional barriers of entry to publication and media. The accessibility of Twitter is also what makes this platform a valuable resource for marginalised groups of people to push policies and engage in politics in ways that they were unable to do prior.
Finding Humanity in Data
With this unique feature in mind I aimed to explore how refugees on Manus Island and Nauru were using the platform to express their views, interests and emotions.
I began doing this by using a Google chrome add-on that archives the history of a particular hash tags –Twitter Archive. I looked up the hash tags #bringthemhere and #letthemstay, the current trending hash tags in Australia used for refugee issues.
In the initial stages of this scrape I looked at how much the content of tweets were shaped by their context, by looking for hash tag patterns in geographic location. However, as this progressed I realised that I was shifting the focus onto the Australian population and away from the refugees. To accompany for this, I realised that maybe I was scraping for the wrong type of data and I needed to focus on a more abstract type of data to render the type of results I wanted.
Mindmap of my process and how my initial area of research actually informed my focus area.
Whilst my search for relevant data in this focus area was fruitless, I found an account which was repeatedly showing up with and IP address from Papua New Guinea. When I clicked on the hyperlink it took me to the page of a 25 year old Iraqi refugee.
When I visited the page, I was invited to follow other refugees who were on twitter and talking about their time and experiences in offshore immigration detention centres.
I documented a selection of posts on each profile which were the most popular via retweet or favoriting. The results of these indicate that twitter users were more responsive to tweets that was organic and original in content and / or personal opinion and/ or personalised through use of emoticons. It was these results that prompted my interest in the use of language and expression as a form of data.
Excerpts from the Twitter page of user @khankha06919739. The user’s language tended to be quite poetic and metaphoric. They used Twitter as a forum to voice their opinions around the conditions and cruelty of offshore detention centres.Excerpts from the Twitter page of user @elahe_zivardar. This user used alot of imagery, often portraying the different peaceful protests that were occuring on Nauru (where they were detained). At times they talked about the lack of fresh fruit and vegetables and how difficult it was to remain healthy when they were so poor.
Excerpts from the twitter page of user @SuchNigel. The content of their tweets is often about feelings and emotions or updates and questions about what’s happening on Manus. One gets the impression from the tweets that there’s not a lot of clarity of information which in turn, fuels discomfort and anxiety.
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Excerpts from the twitter page of user @ManusFad22. Their twitter content is a mixture of football and their daily musings of being on Manus.
Of these profiles I ran an analytics program through to see which words were most common on each of the profiles, what were the most used hashtags, and what time of day they were each posting at.
The results are indicative of the humanity of people in detention; each user has an individual mode of self-expression. This subjectivity of refugees is often erased in the media, which tends to depersonalise refugees and thereby strip them of their identity. Looking at the analytics of these results provide insight to the similarities and differences between the accounts and highlighted the individuality of each refugee as it would for an ordinary person.
Potential Outcomes
As the nature of my research has been predominantly towards representation of refugees in the media vs the media generated by refugees it would be interesting to explore avenues in which I could emphasise the humanity and ordinariness of refugees.
A manner in which I think this could be most effective is by considering the opposite spectrums of similar situations, comparing the spaces of Australian suburbia with Nauru and Manus. In a brainstorm of ways I could do this is looking at physical items like objects, people, space, and abstract items like dreams, ideas, language and feelings.
Image References
Image: Wallman, S. A Guard’s Story, 2014
In order to gain a border understanding of online privacy that happened in people’s life, I looked up Twitter with web-scraping technique. Twitter as a social network is simply bring people closer to their interests and it’s still evolving with various options for its users. The network let users like create a profile, choose whom you would want to follow and post tweets which allow you share your mood and insight on the platform, as well as engage people build conversation around the world. All the tweets of people you follow appear as a shuffled list on your main Twitter page. Businesses have found Twitter to be an effective means of communication with their customers. The network connects businesses with their customers anytime, anywhere. However, it still has limitation of message number, following and follower.
On the other hand, twitter has built a unique function called “ Twitter Advanced Search”, which allow user to tailor search results to specific date ranges, people and more. This makes it easier to find specific Tweets. It been used for people who looking for specific topics and areas that can easy focus on their conversation between same topic. Based on the research, people has started against “privacy information usage” to protect their own information, they believe this is the most expedient way.Therefore, people share on Twitter with representative image, own experience, articles and videos to not only express their positions, but to encourage more people to protect their own online privacy. On the other hand, business also exist as a big part in Twitter Advanced Search that help people dealing with their privacy issues. (See the image below)
(Twitter Advanced Search with key words “commercial online privacy)
(Twitter Advanced Search with key words “commercial online privacy)
Get start of using web-scraping, I set up the key words as “ web personal online privacy”. Most of these tweets are surrounding suggestions and experience with how to protect personal information online to avoid commercial website. Besides, twitter doesn’t have much conversations to communicate the issue specific into the keywords I set up; most of them shared between 2009-2016. At the same time, I have identified how hashtags/key words trend over the time, between 2009-2010, most of people start think about their online privacy and ask for how can they protect the information not be used; after 2010, people described the issue and list “how to control”; in the most recent post, it listed “should you tape over your webcam? personal guide to online privacy”.
( Twitter Advanced Search,”keywords web personal online privacy”, 2016)
Then I reset the hashtags to “web use privacy”. In these tweets, it is clear that personal opinions and positions are significantly less than those advertisings, which are used to explain how people deal with privacy issue. In other words, few tweets posted the position of “People Limit Web Use Due To Privacy Concerns” happened in America. Concerns about privacy and security are discouraging people from posting to social networks, expressing controversial opinions, conducting online banking and shopping from online retailers.
(Twitter Advanced Search, “web use privacy”, 2016)
(Twitter Advanced Search, “web use privacy”, 2016)
It’s interesting to look at is there a video is shared on Twitter, which shows the online privacy secret that some big companies didn’t tell you. The video come up with creepy and strong music, the text put you in a serious atmosphere; engaging and warning people protect their online privacy.
(Vidivo.com 2010)
At the end, the positions and insights from different people all strongly proved the wealth of suggestions and experience through social media. It can help us get a deeper understanding of the seriousness of the issues, as well as provide more viable solutions. For future exploration and my design project, I would like using this data -scarpingtechnique to generate a range of privacy data flow and make them visually express the seriousness of online privacy.
5 point summary:
Twitter Advanced Search help people easily gather information and research on social media.
People has stand out to against companies use their personal information without their concern.
More effective solutions/suggestions surrounding online privacy can be found out with web-scraping technique
Concerns about privacy and security are discouraging people from posting to social networks
A commercial website need post a privacy policy if it collects personally identifiable info
Reference
Vidivo.com 2010, Online Privacy Secrets EXPOSED Commercial – What Google Isn’t Telling Us, video recording, YouTube, viewed 3 September 2016,<http://www.youtube.com/watch?v=QYP_hZmcRgg>.
Twitter is a social media platform that allows users to send and receive Tweets. Tweets are short messages of up to 140 characters that can also contain images, videos and links. Tweets are limited to 140 characters so they can be sent via SMS. This ensures that users can stay engaged with the service, even if they do not have access to the internet (Twitter 2016). Although Twitter may function similarly to an Instant messaging client it is far from it. Unlike a messaging application where the messages become unavailable when the program is closed, communications sent through twitter are permanently archived (Smith 2012). Moreover, unlike other social media platforms such as Facebook and LinkedIn, every profile on Twitter is set to public by default. This means that users can view the activity of almost anyone on the site (Twitter 2016). This makes Twitter a great tool to engage in a conversation with people from around the world. Twitter helps facilitate this dialogue through the inclusion of hashtags; metadata keyword labels that allow users to filter tweets by a specific theme (Smith 2012). This functionality is crucial to Twitter’s success and makes it easy for disparate groups of people come together to discuss issues in an open and approachable way.
Open ended queries like this returned far better results than narrow searches
People are generally unaware of how much information they contribute to digital systems. This was something I identified from my primary research, and was able to explore further through data scraping techniques. Using Twitter’s advanced search I began by investigating how people responded to targeted advertisements, such as those found on Facebook and Google. In this instance the overwhelming majority of Twitter users expressed concern over how these companies were able to connect seemingly unrelated events to serve them highly targeted advertisements. This not only helped identify some of the ways in which companies can collect data, but also identified an important cognitive bias; that users are unlikely to understand or question the ramifications of granting access to their personal data until they see how powerfully it can be harnessed. With that being said, a small number of user’s also chalked up uncannily specific advertisements to coincidence. This indicates that these individuals don’t believe companies have the power or authority to collect and analyse data on such a scale. In addition to text analysis, I was also able to discover that the majority of people engaged in this debate were from the US, which is not surprising given their widespread access to telecommunications technology.
A sample of the results returned from my Twitter advanced search
To develop this research visually, it would be interesting to look at how connecting data points can reveal new information about an individual. As stated above this is something that is generally not well understood, and would be interesting, albeit challenging to explore visually. One way this could be achieved is through overlaying a person’s electronic footprint on a map. Examples of information that could be used to paint a picture of this person’s day include EFTPOS purchases, Opal card activity and the use of a student ID card and its associated electronic login. As you can see with just a few data points, it would be very easy to begin to piece together a very detailed picture of this person and their activity over the course of the day. Alternatively it might also be interesting to look at the variety of different way your phone or laptop could be spying on you. Examples of this include GPS signals to track you location, cookies to track your activity online and accelerometer data to track your movement. While this is not as strongly connected to the idea of unwittingly contributing data to digital systems, it does relate to my earlier secondary research on WikiLeaks and the NSA.
People are growing increasingly suspicious of how much data is being collected about them without their consent.
The commercial value of data profiling is driving the development of more invasive collection techniques.
Most users do not read the terms of service outlining data collection policies when registering for online services.
Targeting advertising is becoming increasingly accurate as technology permeates more and more aspects of our lives.
Online privacy is very much a western issue at the moment, although it will become more relevant as developing countries become more connected.
My specific topic is the association between sedentary lifestyle and obesity. Therefore, I searched using keyword ‘Obesity’, ‘Fat’, ‘Sedentary’, and ‘Lifestyle’ at first.
Emergent Practices 
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