Twitter Collection and Analysis Toolkit (BU-TCAT)

Visualizing Ebola on Twitter

Co-mentions in 5,240,900 ‘Ebola’ Tweets graphed into 1,000 nodes with 2,270 directed edges

The BU-TCAT allows Boston University students and faculty–and even off campus researchers–to collect Tweets off the STREAM API (the so-called “gardenhose” access to Twitter) and then process the data for network analysis and visualization in Gephi with just one click.  With this free open-source software,  social data in the millions of units is quickly and easily sorted by algorithms to find people or items of importance on Twitter.  Dr. Jacob Groshek, the BU-TCAT administrator and social data expert, offers workshops for network visualizations using the BU-TCAT.  Contact him @jgroshek on Twitter for more information or to request a workshop.

As a resource to Boston University and the broader research community, the BU-TCAT opens up a host of analytic options that require absolutely no programming or software knowledge.  Click here for free access to the TCAT and then you can just point and click through the many detailed analysis options, which include:

  • Timeline of Twitter activity, with minute-by-minute timestamping
  • Tweet statistics like hashtag and retweet frequencies, geocoding and unique users
  • Specific user stats: number of friends, followers, favorites, and verification
  • Activity metrics such as user visibility by mention frequency
  • Hashtag frequency, hashtag-user activity, word and identicial Tweet frequency
  • Tweet exports–get them all or sample a random selection
  • Lists of individual retweets with metadata
  • Export only geocoded Tweets and Tweet ids
  • Network graphs by mentions,  co-hashtagging, and hashtag-user graphs
  • Cascades, alluvial diagrams, and associational profiles

Unlike many other types of Twitter collection systems or software, BU-TCAT searches do not run out or expire until they are turned off.  In the last two months the BU-TCAT system has archived approximately 110 million Tweets (and counting), on topics such as Ferguson, selfies,data journalism, and the Massachusetts gubernatorial race.



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