Research Proposal: Social Data Analysis of the Feminist Movement


My passion for digital media lies in its limitless nature. Entire conversations about a topic exist publicly online. There’s so much to be learned from these conversations, but generally analysis only goes so far to determine that a topic is trending, yet neglects to tell us what is really being said. Thus there is a gap in the market for issue-mapping in sociocultural online conversations – a gap which is screaming my name.

I read an article during the summer holidays on issue mapping and social media controversies, which focused on #GamerGate as a social case study. I was completely inspired by the research methodology; Burgess went beyond the trending topics algorithm presented on Twitter (which is limited to identifying what is being spoken about – without detail – and the rate at which it spreads between nodes) and used various issue mapping tools to generate an understanding of what was actually being said about GamerGate on a global scale, which allowed the researchers to gain a clear and vast understanding of the players in the debate.

Imagine this; you’re sitting at a table in a busy cafe. The woman sitting at the table behind you has said “the feminists” in the midst of her conversation. As you walk out to pay the bill, you hear the word being spoken over and over, throughout the different tables, by all different people. Curiosity becomes you; who are the feminists? What are people saying about them? Why are they talking about feminism now?

Internet environments are structured similarly; we know that a topic is trending, but we don’t know what is being said, where the influence comes from or who the instigators or leaders are. Burgess’s article dives into the gaps of information analysis and opened up a new world of opportunity for me. As a result of this I intend to look at the conversation as a whole on Twitter, instead of designing a survey or organising a focus group of a limited sample.

To scope this project, I will focus on the #heforshe campaign, and analyse the conversation surrounding it on twitter. I will map various responses in relation to different stimuli and media events (such as Emma Watson‘s UN speech in 2014), and over time, using open source programming, sentiment analysis and tools such as keyhole.

(source) Sentiment Analysis measures the positive/negative words in a tweet to determine direction of conversation

As an aspiring social media analyst, this project will hopefully be the first of many, and provide me with an insight into the various tools and methodologies of social media data analysis to determine the effectiveness of a digital campaign.



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