My talk is about the ways social network analysis can reveal important patterns in social media.
CHARTING COLLECTIONS OF CONNECTIONS IN SOCIAL MEDIA:
CREATING MAPS AND MEASURES WITH NODEXL
The requested date range was from Tuesday, 01 April 2014 at 00:00 UTC through Sunday, 08 June 2014 at 23:59 UTC.
The tweets in the network were tweeted over the 67-day, 4-hour, 35-minute period from Tuesday, 01 April 2014 at 00:26 UTC to Saturday, 07 June 2014 at 05:01 UTC.
There is an edge for each “replies-to” relationship in a tweet, an edge for each “mentions” relationship in a tweet, and a self-loop edge for each tweet that is not a “replies-to” or “mentions”.
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 edge weight values. The edge widths are based on edge weight values. The edge opacities are based on edge weight values. The vertex sizes are based on followers values. The vertex opacities are based on followers values.
Top 10 Vertices, Ranked by Betweenness Centrality:
Top URLs in Tweet in Entire Graph: