Connected Action

Sociology and the Internet, Social Media, Networks and Mobile Social Software

#occupywallstreet NodeXL SNA Twitter Map for 8 October 2011

October 8th, 2011 by Marc Smith · 1 Comment

The #Occupywallstreet movement is growing and lots of activity is taking place in social media.  Here is a map of the connections among the people who recently tweeted the term “#occupywallstreet” on 8 October 2011.


Link: www.flickr.com/photos/marc_smith/6225446144/

Each user is scaled by numbers of followers (with outliers thresholded). Connections created when users reply, mention or follow one another.

See: occupywallst.org/

A larger version of the image is here: www.flickr.com/photos/marc_smith/6225446144/sizes/l/in/ph…

Top most between users:
@maddow
@motherjones
@aclu
@zerohedge
@mmfa
@spread4freedom
@diggrbiii
@angelsavant
@marychastain
@katiepavlich

Graph Metric: Value
Graph Type: Directed
Vertices: 1000
Unique Edges: 3835
Edges With Duplicates: 916
Total Edges: 4751
Self-Loops: 1109
Connected Components: 311
Single-Vertex Connected Components: 301
Maximum Vertices in a Connected Component: 678
Maximum Edges in a Connected Component: 4327
Maximum Geodesic Distance (Diameter): 9
Average Geodesic Distance: 3.283708
Graph Density: 0.003408408
NodeXL Version: 1.0.1.179

More NodeXL network visualizations are here: www.flickr.com/photos/marc_smith/sets/72157622437066929/

Tags: Collective Action · Common Goods · Community · Foundation · Measuring social media · Network visualization layouts · NodeXL · Politics · Research · SMRF · Social Interaction · Social Media · Social Media Research Foundation · Social network · Social Network Analysis · Social Roles · Sociology · Visualization

1 response so far ↓

  • 1 Nick Gramsky // Nov 15, 2011 at 9:27 pm

    Awesome visualization Marc! I visualized the same network between 11/12/11 – 11/13/11 and it can be seen here http://http://gramsky.blogspot.com/ I’m still working on making the layouts as beautiful as you have. I did, however, use the ‘Group in a box’ method and hopefully did so in the same manner. I’m not showing the large clusters as your visualization shows but rather an increase in a small number of clusters. Unsure if I did something differently or if the structure of the network has evolved over the past month. Either way, interesting to see the same network one month apart.

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