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Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
Keepr presentation at MIT CMSW
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Keepr presentation at MIT CMSW

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audio and live blog notes http://cmsw.mit.edu/liveblog-hong-qu-keepr/

audio and live blog notes http://cmsw.mit.edu/liveblog-hong-qu-keepr/

Published in: Technology, Business
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Transcript

  • 1. Keepr Algorithm for Extracting Entities, Eyewitnesses and Amplifiers Hong Qu September 19, 2013
  • 2. http://twitpic.com/135xa https://twitter. com/jkrums/status/1121915133
  • 3. http://www.telegraph.co.uk/technology/twitter/4269765/New-York-plane-crash-Twitter-breaks-the-news-again.html
  • 4. http://www2.sims.berkeley.edu/courses/is290-2/f04/sched.html
  • 5. https://twitter.com/hqu/status/1745171763
  • 6. Humans vs Machines Pattern RecognitionValue Judgment
  • 7. Computers count really, really fast!
  • 8. What is a Tweet? 140 characters: ● words ● @user mentions ● #hashtags ● links
  • 9. Hows does Keepr process tweets? 140 character * 100 tweets = 14,000 characters ❏ Parse it ❏ Count it ❏ Visualize it ❏ Zoom in ❏ Archive it
  • 10. https://canvas.instructure.com/courses/812708/assignments/syllabus Natural Language Processing
  • 11. Humans are way better at at making value judgements and telling stories
  • 12. Social media and the Boston bombings: When citizens and journalists cover the same story
  • 13. Keepr’s Algorithm ➔ Entity extraction ◆ Topics ➔ Media extraction ◆ images, videos ➔ Link expansion ◆ articles ➔ Conversation analysis ◆ @ mentions ◆ source discovery ◆ amplification velocity ➔ Source verification ◆ geo-location ◆ social media profiles
  • 14. Topic Extraction by Term Frequency http://trimc-nlp.blogspot.com/2013/04/tfidf-with-google-n-grams-and-pos-tags.html
  • 15. https://twitter.com/hqu/stawww.cs.cornell.edu/home/kleinber/bhs. pdftus/1745171763
  • 16. Journalists want ❏ Source discovery and curation ❏ Passive monitoring and alerts ❏ Saving and archiving ❏ Visualizations ❏ Parity with TweetDeck user interface
  • 17. People want “I want to catch up with a summary of key information about the breaking news story.” I want to get a list of Twitter accounts who are official organizations related to that story.
  • 18. My Musing
  • 19. What’s next for keepr? ➔ refine algorithm ➔ source classification ➔ conversation analysis and visualization ➔ archiving search results and tweets Rolling out a Beta program for newsrooms Sign up at www.keepr.com/beta
  • 20. https://github.com/hqu/keepr
  • 21. Verification Resources ● Verifying Social Media Content ● verificationjunkie.tumblr.com ● BBC processes for verifying social media content ● Storyful’s validation process ● InformaCam

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