Visualizing ‘Queer Exchange’ Friendships

I am increasingly interested in the social networks of queers, broadly and self-defined. One of the largest queer groups on Facebook that I know of is the Facebook group Queer Exchange with 7,855 members as of December 1, 2013. Each node or dot represents a person and the lines or edges indicate the friendships between them. Rather than a top-down culture, Queer Exchange repeats the interwoven and overlapping descriptions of queer spaces and lives that have described lgbtq life across cities, states, and times. In other words, many cultures often demonstrate relationships and dynamics that show some dominant voices overtaking others, or friends being connected to only one other person so they wander on the periphery. Instead this graph shows an interwoven society.

If you click the here or on the graph below, you can interact with the social network analysis graph of Queer Exchange I created.

User friendships on the Facebook group Queer Exchange as of December 1, 2013.  The 7,855 group members indicates how connections between queers overlapping rather than built replicating top-down cultures of interchange and expression. Created by Jen Jack Gieseking CC BY-NC 2013
Click on the image above to interact with this social network analysis.

Social media sites such as Facebook and Tumblr have long been and increasingly been “free” sites where lgbtq people can create pages or sites for organizations, events, and shared interests. I say “free” to say these sites seem to have no costs but involve handing over data that is of incredible value to these corporations. So: with good, bad too. Om shanti. There is so much more to visualize here, and grows from my previous and future work on visualizing lesbian-queer archives.

I know it may be frustrating to some that names/user ids are anonymized but this is key to privacy. Furthermore, the application I used to create this graph anonymizes this information in advance. Thankfully.

Social network analysis (SNA) graphs can be incredibly unclear and opaque, and I have written on this topic before in my post, “Opaque is Being Polite: On Algorithms, Violence, & Awesomeness in Data Visualization.” But how did I make this? If you are ready to jump into SNA, I highly recommend Gephi which I used to build this graph. In order to gather the information to make this graph, I used the Netvizz application on Facebook. In order to embed this graph into my website, I turned to the Sigma.js export plugin for Gephi and the directions I found in this lovely post from the Oxford Internet Institute. Enjoy networking!

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