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Enron Email visulisation at the Big Data InfoVis summer school

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Team Fir
Claire Jones
Daniel Rough
Gavin Hales
Lisa Koeman

Published in: Business, Technology
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Enron Email visulisation at the Big Data InfoVis summer school

  1. 1. Visualisation of the Enron dataset the Enron dataset Claire, Daniel, Gavin and Lisa
  2. 2. Enron: background • American energy, com- modities, and services company • Bankrupt in 2001: accounting fraud • Many executives ended up in prison
  3. 3. Enron: dataset • ~500,000 mails • 158 employees • Social security numbers, bank details, etc. taken out • Only large, public mail dataset available, containing real e-mails
  4. 4. Our concept • Dataset contains profanity • Group mails by threads • Calculate profanity factor for different threads • Plot profanity of conversations on timeline
  5. 5. Initial sketch
  6. 6. Approach • Focus on ‘sent’ folder, to avoid duplicates • Group mails by subject (i.e. identify threads) • Taken out blank subjects • Retrieve basic information: • Sender • Timestamp
  7. 7. Approach • List of swearwords • Count frequency of swearwords per thread
  8. 8. Data analysis • Initially used AWS, too time-consuming for what we needed • Ended up using Python • JSON output
  9. 9. Visualisation • Made use of Highcharts.js • Combined with TagCanvas (HTML5)
  10. 10. Demo

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