Self Promoted Media
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.

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.



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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
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