DCDC

November 13 at 6pm: Data Community DC Workshop on Analyzing Social Media Networks using NodeXL

Data Community DC Logo

NodeXL Logo

I am excited to have the opportunity to present a NodeXL workshop at the DC Data Community on November 13th at 6pm in Washington, D.C.

In this session I will describe the ways NodeXL can simplify the process of collecting, storing, analyzing, visualizing and publishing reports about connected structures.

2013-SMRF-NodeXL-SNA-5 steps for Social Media Network Analysis

For example, this is a map of the connections among the people who recently tweeted about the DataCommunityDC Twitter account was created with just a few clicks and no coding:

DataCommunityDC Twitter NodeXL SNA Map and Report for Tuesday, 05 November 2013 at 15:15 UTC

This graph represents a network of 67 Twitter users whose recent tweets contained “DataCommunityDC“, taken from a data set limited to a maximum of 10,000 tweets. The network was obtained from Twitter on Tuesday, 05 November 2013 at 15:15 UTC.
The tweets in the network were tweeted over the 7-day, 16-hour, 4-minute period from Monday, 28 October 2013 at 22:38 UTC to Tuesday, 05 November 2013 at 14:42 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 network has been segmented into groups (“G1, G2, G3…”) and each group is labeled with the words most frequently used in the tweets from the people in that group.
The size of each Twitter user’s profile picture represents the log scaled value of their follower count.
Analysis of the network location of each participant reveals the people in key locations in the network, people at the “center” of the graph.

They are:

@datacommunitydc
@datafest2013
@gabosama
@harlanh
@mlh_holmes
@terebouza
@greglinch
@intridea
@gilpress
@katiestriff

The top URLs mentioned in this network were:

 

Top URLs in Tweet in Entire Graph:
http://www.washingtonpost.com/national/hackathon-aimed-at-finding-ways-to-help-migrants-those-researching-migration/2013/11/01/30a3b054-4318-11e3-b028-de922d7a3f47_story.html
http://datacommunitydc.org/blog/2013/09/data-community-music-scene/
http://www.youtube.com/watch?v=czUHoy4rJZU
http://datacommunitydc.org/blog/2013/07/weekly-round-up-data-science-metro-map-big-data-workers-prescriptive-analytics-and-knewton/
http://datacommunitydc.org/blog/2013/11/hadoop-for-data-science-a-data-science-md-recap/?utm_source=rss&utm_medium=rss&utm_campaign=hadoop-for-data-science-a-data-science-md-recap
http://datacommunitydc.org/blog/2013/11/ten-simple-rules-for-reproducible-computational-research-an-excellent-read-for-data-scientists/?utm_source=rss&utm_campaign=ten-simple-rules-for-reproducible-computational-research-an-excellent-read-for-data-scientists&utm_content=bufferd23b3&utm_medium=twitter
http://www.meetup.com/BusinessIntelligentsiaDC/
http://computopics.dcacm.org/2013/10/31/travelling-salesmen-qa-with-director-timothy-lanzone/?utm_content=buffer007e2&utm_source=buffer&utm_medium=twitter&utm_campaign=Buffer
http://www.nature.com/scientificdata/?utm_content=buffer88b38&utm_source=buffer&utm_medium=twitter&utm_campaign=Buffer
http://www.theverge.com/us-world/2013/11/4/5066300/shotspotter-analyzes-sound-waves-detects-crime