By Natalie Borghi
Through the use of primary and secondary sources over the past five weeks, I’ve gained an extensive insight into the issue of gender equality in the Australian workplace. This included the use of articles, scholarly sources, images and interviews with individuals between 18-24 years.
Choosing A Social Media Platform
The next stage of research required collecting and analysing data from one social media platform, in which I have chosen Twitter. Used as a social networking site, Twitter allows users to send short messages, known as “tweets,” within 140 characters. Tweets can either be just text, incorporate “hashtags,” or link to external sites, which can also be “re-tweeted” by other users.
I chose Twitter for two reasons; Firstly, the site was originally used by a ‘younger’ audience, however in recent times, the audience has broadened as more businesses have started using it as a promotional platform. Secondly, through the use of hashtags and text-based posts, it’s relatively easy to find trends surrounding current issues.
Utilising the software, Twitter Archiver, I was able to custom search Twitter for specific tweets, which were then displayed on a Google Docs page. Information such as the person’s username, their tweet’s content, the device they tweeted from, retweets and location are listed, allowing for thorough data analysis.
Creating a Twitter Rule
When setting up a search, Twitter Archiver allows for key words, hashtags, usernames or locations to be selected to narrow down searches. Looking into gender equality and the pay gap within the Australian workplace, I conducted multiple searches interchanging words between “gender pay gap,” “women,” “fair,” “confidence,” “workplace,” and “Australia.” I set the language to English and removed any “retweets.”
A broad selection of tweets were produced, from opinions, statistics, quotes and company promotions, such as the following:
https://twitter.com/churchofwulf/status/746507610099060736?lang=en (need to reference)
However, I found the more specific I got, the harder it was to find results. Each search only produced approximately five tweets. This led me to more simplified searches such as “#genderequality” or “pay gap.” I thought it’d be interesting to observe and compare how Australia uses these terms, so I conducted multiple searches located in each Capital City of Australia.
Using pie charts, I’ve visualised my findings through the four categories I observed earlier, opinions, facts, quotes, and promotions.
As Twitter is generally about thought sharing, it wasn’t too surprising that majority of my findings were opinions, however I did find it interesting noticing the varied amounts of facts, quotes and promotions that were also present. I found Sydney and Melbourne produced the most tweets for each search, compared to other cities, who either produced little to no results, as evident in the ‘#genderequality’ results. If there weren’t any results, I did not include a chart for that city. The lack of results could be for a couple of reasons; either tweets within those areas haven’t been location set, or these topics aren’t tweeted about. However I believe it’s more of the former.
Overall, I found this to be an insightful exercise. Compared to the image and text results of a general twitter search, it was especially useful using Twitter Archiver, which provided a list of text-only results. There were multiple possibilities for how the information could be analysed, however by observing how these key words are used across Australia helps to indicate which states are more actively involved in the issue.