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Tracking the dynamics of social
communities - Visualising altering word
       clouds of Twitter groups




     Wolfgang ...
What is Twitter?
• 140 characters                         • @Mentions (Replies) and Retweets

• from mobile, client or web...
Who uses this?
                                                              Different kind of people
http://www.flickr.co...
Learning ?




                                                       © Wolfgang Reinhardt, University of Paderborn
     •...
© Wolfgang Reinhardt, University of Paderborn
                     Thx for the last two slides
                           ...
EduMedia 2009
Overview




Wolfgang Reinhardt
                7




                     © Wolfgang Reinhardt, University of Paderborn
Wolfgang Reinhardt
                                                                     Share in communication




       ...
Statistics




Wolfgang Reinhardt
                9




                     © Wolfgang Reinhardt, University of Paderborn
What‘s behind?
Analysis application
• inspect communication from communities on Twitter


• goal: track the changes within the community
...
Mashup ?
• Twitter API


• Yahoo Term Extraction Web Service API


• providing enriched data via API


   • JSON encoded

...
Conclusion / Outlook
• tool for analysing and visualising group communication on Twitter


   • main statistical data abou...
Conclusion / Outlook
• enhance qualitative evaluation


   • named entities


   • sophisticated metrics


   • visualize ...
Thank you
Want to know more?
http://twitter.com/wollepb
http://isitjustme.de
http://artefact-actor-networks.net




      ...
Image sources
•   http://medyasia.com/wp/wp-content/uploads/2009/08/bluebird_1680x1050.jpg



•   http://de.fotolia.com/id...
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Tracking the dynamics of social communities - Visualising altering word clouds of Twitter groups

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Tracking the dynamics of social communities - Visualising altering word clouds of Twitter groups

  1. 1. Tracking the dynamics of social communities - Visualising altering word clouds of Twitter groups Wolfgang Reinhardt - University of Paderborn
  2. 2. What is Twitter? • 140 characters • @Mentions (Replies) and Retweets • from mobile, client or web interface • #Hashtags • Followers • Open API • Direct messages © Wolfgang Reinhardt, University of Paderborn 2 Wolfgang Reinhardt
  3. 3. Who uses this? Different kind of people http://www.flickr.com/photos/cogdog/601808418 using microblogs Java et al, 2007 © Wolfgang Reinhardt, University of Paderborn Exchanger Daily Chatter http://flickr.com/photos/thomcochrane/416206133/ Communicator Reporter 3 Wolfgang Reinhardt
  4. 4. Learning ? © Wolfgang Reinhardt, University of Paderborn • informal learning • microsharing • personal http://flickr.com/photos/thomcochrane/416206133/ 4 Wolfgang Reinhardt
  5. 5. © Wolfgang Reinhardt, University of Paderborn Thx for the last two slides 5 Wolfgang Reinhardt
  6. 6. EduMedia 2009
  7. 7. Overview Wolfgang Reinhardt 7 © Wolfgang Reinhardt, University of Paderborn
  8. 8. Wolfgang Reinhardt Share in communication 8 © Wolfgang Reinhardt, University of Paderborn
  9. 9. Statistics Wolfgang Reinhardt 9 © Wolfgang Reinhardt, University of Paderborn
  10. 10. What‘s behind?
  11. 11. Analysis application • inspect communication from communities on Twitter • goal: track the changes within the community • personal and topic networks • hashtags © Wolfgang Reinhardt, University of Paderborn • usernames • extract content and statistical data 11 Wolfgang Reinhardt
  12. 12. Mashup ? • Twitter API • Yahoo Term Extraction Web Service API • providing enriched data via API • JSON encoded © Wolfgang Reinhardt, University of Paderborn • to be enhanced in upcoming versions • using geo location • using multiple extractors 12 Wolfgang Reinhardt
  13. 13. Conclusion / Outlook • tool for analysing and visualising group communication on Twitter • main statistical data about the group • tracking dynamics • create widgets and incorporate in other systems © Wolfgang Reinhardt, University of Paderborn • conference pages • course-wikis • PLEs 13 Wolfgang Reinhardt
  14. 14. Conclusion / Outlook • enhance qualitative evaluation • named entities • sophisticated metrics • visualize communications among users © Wolfgang Reinhardt, University of Paderborn • include links in the evaluation • semantic closeness of tweets / persons • Artefact-Actor-Networks 14 Wolfgang Reinhardt
  15. 15. Thank you Want to know more? http://twitter.com/wollepb http://isitjustme.de http://artefact-actor-networks.net Wolfgang Reinhardt University of Paderborn Institute of Computer Science Working Group Didactics of Informatics http://ddi.upb.de
  16. 16. Image sources • http://medyasia.com/wp/wp-content/uploads/2009/08/bluebird_1680x1050.jpg • http://de.fotolia.com/id/3805293 • http://www.flickr.com/photos/leapfrog_photo/2532068489 • http://upload.wikimedia.org/wikipedia/commons/c/c4/Old_door-dakhla-egypt.JPG • http://www.flickr.com/photos/cogdog/601808418 • http://flickr.com/photos/thomcochrane/416206133/ 17

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