There will be a 3 hour Q&A and hands-on tutorial on the use of NodeXL and broadly on social media network analysis. We will focus on the process of collecting, storing, analyzing, visualizing, and sharing insights into social media network graphs.
Many thanks to Maksim Tsvetovat (@maksim2042) for arranging the location.
Bring your SNA, social media, social network, and NodeXL questions along with sample data sets!
Come hear about NodeXL features that make automating network data collection, analysis, visualization and publication simple and easy. Get daily reports on the social networks that matter to you!
I will talk about the upcoming features releasing in NodeXL (auto update, new layouts, better importers for Twitter, Facebook, Wikis, and more) and take your requests.
If you would like to attend please complete this form:
The talk will focus on the easy to follow steps needed to create social media network maps and reports automatically from services like Twitter, Facebook, YouTube, Flickr, email, blogs, wikis, and the WWW. Here is a sample network map of the term #bigdataprivacy:
The graph represents a network of 248 Twitter users whose recent tweets contained “#bigdataprivacy”, or who were replied to or mentioned in those tweets. The tweets in the network were tweeted over the 6-day, 10-hour, 29-minute period from Tuesday, 25 February 2014 at 14:36 UTC to Tuesday, 04 March 2014 at 01:06 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 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:
@whitehouseostp, @mit, @mit_csail, @steve_lockstep, @aureliepols, @dbarthjones, @digiphile, @stannenb, @djweitzner, @mikaelf
This is a sample NodeXL graph that represents a network of 106 Twitter users whose recent tweets contained “passbac”. The network was obtained on Wednesday, 30 January 2013 at 01:09 UTC. There is an edge for each follows relationship. 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 tweets were made over the 7-day, 5-hour, 32-minute period from Tuesday, 22 January 2013 at 17:40 UTC to Tuesday, 29 January 2013 at 23:12 UTC.
Learn to make your own network maps of social media at PASSBAC 2013!