Gender and Oppression Online: A Discussion about Marquette's Tweeting Habits
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Our cyber identities are increasingly tied to our physical, emotional, and existential selves. Our social technologies shape “who” we spend our time with, and more importantly, how. Who and what we choose to be online reflects a great deal about our own identity, particularly with respect to gender.
And I want to explore more of how online comments and interactions between gender identities take shape.
More specifically, I want to look at online conversations on Marquette University’s campus to see if patterns of behavior diverge based on gender identities. Since so much information and data is widely distributed and available online, can this so-called gender identity be measured and analyzed?
To tackle this question, I’ve been looking at tweets on Marquette University’s campus over the past month. I used Twitter’s API and some Open Source Software libraries to scrape tweets from Twitter, analyze their sentiment (a measure of how positive or negative a sentence/word is), and parse topics from sentences. I built a web application to aggregate, analyze, and visualize this data using a remote database (you can see more of the technical bits/source code here).