April 13th 2012 – University of Wisconsin, Madison, School of Journalism and Mass Communication event “Ethics and Elections: Media, Money and Power” – panel “Tweets and Votes: Elections in a Social Media Age”

I will speak on a panel on April 13th at the University of Wisconsin, Madison, at an event sponsored by the School of Journalism and Mass Communication.   The event “Ethics and Elections: Media, Money and Power” will feature “panels, break-out workshops, and debates on the role of political advertising, media “fact checking” on candidate statements, electoral coverage and social media, tracking political donations, and proposals on how to “clean up” the political process.”

A panel from 1:40pm – 2:40 pm on Tweets and Votes: Elections in a Social Media Age will feature panelists Ryan Gallentine, Thomas Keeley, Kathleen Culver and Marc Smith.

I will speak about the results of collecting, analyzing and visualizing the collections of connections that form in political discussions in social media.

For example, this is a map of the connections among the people who recently tweeted about Scott Walker.

The graph represents a network of up to 1000 Twitter users whose recent tweets contained “scott AND walker”. The network was obtained on Friday, 13 April 2012 at 07:40 UTC. There is an edge for each “replies-to” relationship in a tweet. There is an edge for each “mentions” relationship in a tweet. There is a self-loop edge for each tweet that is not a “replies-to” or “mentions”. The earliest tweet in the network was tweeted on Thursday, 12 April 2012 at 03:32 UTC. The latest tweet in the network was tweeted on Friday, 13 April 2012 at 04:12 UTC.

The graph is directed.

The graph’s vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.

The edge colors are based on relationship values. The vertex sizes are based on followers values.

Overall Graph Metrics:
Vertices: 1000
Unique Edges: 9789
Edges With Duplicates: 958
Total Edges: 10747
Self-Loops: 714
Connected Components: 166
Single-Vertex Connected Components: 156
Maximum Vertices in a Connected Component: 814
Maximum Edges in a Connected Component: 10505
Maximum Geodesic Distance (Diameter): 8
Average Geodesic Distance: 2.912947
Graph Density: 0.00967067067067067
Modularity: 0.341382

Top 10 Vertices, Ranked by Betweenness Centrality:
@huffingtonpost
@thenation
@edshow
@usrealitycheck
@huffpostpol
@nicholsuprising
@ezkool
@spudlovr
@thewiremagazine
@truthteam2012

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