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Twitter news-credibility

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Twitter news-credibility

  1. 1. !"#$%‫+*! ا) ا%$#( ا‬ Social Media A Systematic Methodology as a Credible for Estimating the Source Credibility of Twitter of News? StreamsTuesday, November 1, 11
  2. 2. !"#$%‫+*! ا) ا%$#( ا‬ Social Media The Traditional Media has as a Credible obviously decided to Source classify SM as a primary of News? source of NewsTuesday, November 1, 11
  3. 3. Tuesday, November 1, 11
  4. 4. We choose Twitter because: * fastest * most viral * strong APIs * extremely popular * rising numbersTuesday, November 1, 11
  5. 5. Tuesday, November 1, 11
  6. 6. Tuesday, November 1, 11
  7. 7. Can we verify the credibility of a post?Tuesday, November 1, 11
  8. 8. Can we verify Yes the credibility & of a post? NOTuesday, November 1, 11
  9. 9. Can we verify Yes journalistic verification methods the credibility & of a post? NOTuesday, November 1, 11
  10. 10. Can we verify Yes journalistic verification methods the credibility & of a post? NO “cannot be verified independently”Tuesday, November 1, 11
  11. 11. Nevertheless ... The Media tries to verify the credibility of posted stories?Tuesday, November 1, 11
  12. 12. ➡ great deal of experience The ➡ the sheer volume of tweets Verification is time consuming Process ➡ hard to quickly identify a is Difficult & scoop very time ➡ technical limitations ➡ inefficient twitter search consuming ➡ inefficient refresh rateTuesday, November 1, 11
  13. 13. Tuesday, November 1, 11
  14. 14. What we 100s - 1000s of tweets being filtered automatically want to offer from noise through a the media preselection processTuesday, November 1, 11
  15. 15. Tuesday, November 1, 11
  16. 16. What is the 1. Understanding how Automated people evaluate tweets individually Preselection 2. Adding metrics to the Process evaluation Based on? 3. Applying probability algorithmsTuesday, November 1, 11
  17. 17. 1. Understanding how people evaluate tweets individually as individuals we want to: Why Do People ➡ to post only true stories Evaluate ➡ to retain or grow our follower-ship Users in the ➡ remain popular First Place? ➡ be seen as an authorityTuesday, November 1, 11
  18. 18. 1. Understanding how people evaluate tweets individually we analyze the ... How do we as ➡ user individuals ➡ community ➡ interaction evaluate ➡ attitude / typical behavior tweets? ➡ set of morals ➡ topics ➡ influenceTuesday, November 1, 11
  19. 19. 1. Understanding how people evaluate tweets individually What is the result of We want to identify if a user evaluating an is qualified to make the statement just posted. individual?Tuesday, November 1, 11
  20. 20. Tuesday, November 1, 11
  21. 21. 1. Understanding how people evaluate tweets individually The more influential a user Our Thesis the higher the probability (part one): that news posted by this user is credibleTuesday, November 1, 11
  22. 22. 2. Adding metrics to the evaluation Evaluation ➡ Klout The community around the metrics user and the interaction with this community: number of followers, their influence, pro users mentions, retweets ... also check ➡ Peerindex social influence The topics the user usually tweets, the topics of the services community around the users, the topics of conversationsTuesday, November 1, 11
  23. 23. 2. Adding metrics to the evaluation ➡ They have limitations Are these ➡ They have flaws services ... but reliable? ➡ They supply an excellent probability value / indexTuesday, November 1, 11
  24. 24. 2. Adding metrics to the evaluationTuesday, November 1, 11
  25. 25. 2. Adding metrics to the evaluation Can We MeasureTuesday, November 1, 11
  26. 26. 2. Adding metrics to the evaluation Can We Measure Credibility?Tuesday, November 1, 11
  27. 27. 2. Adding metrics to the evaluation Can We ➡ Credibility itself: NO Measure ➡ Probability: YES Credibility?Tuesday, November 1, 11
  28. 28. 3. Applying probability algorithms ➡ take their twitter seriously ➡ feel responsible about posting and reposting true Tweet stories Propagation ➡ act as an evaluation point There is clear in the propagation of a indication that story influential users: ➡ increase the probability of a story being true by an measurable incrementTuesday, November 1, 11
  29. 29. 3. Applying probability algorithms The more influential the user Our Thesis the higher the probability (part two): that news posted by this user is credibleTuesday, November 1, 11
  30. 30. 3. Applying probability algorithms Tweet Propagation ✜ ✜✜ ✜✜✜ This schematic is ridiculously over simplified. The true probability increase will be based on probability theory algorithmsTuesday, November 1, 11
  31. 31. twitter stream Our Proposed System Will Offer an Alternative View of the Twitter StreamTuesday, November 1, 11
  32. 32. probability value on top of the twitter stream ✜ ✜✜ Our Proposed System Will Offer an Alternative View of ✜✜ the Twitter Stream ✜✜✜✜Tuesday, November 1, 11
  33. 33. probability value on top of the twitter stream ✜ ✜✜ ✜✜ ✜✜✜✜ ✜ ✜✜✜ ✜✜ Our proposed ✜✜✜✜ ✜ System Will Offer ✜✜✜ ✜✜ a Novelty! ✜✜ ✜ The Credibility INDEX ✜✜ ✜✜ ✜ ✜✜✜ ✜✜ ✜✜✜✜ ✜Tuesday, November 1, 11
  34. 34. probability value on top of the twitter stream ✜ ✜✜ ✜✜ ✜✜✜✜ ✜ ✜✜✜ ✜✜ The Media Now ✜✜✜✜ Have Dozens Instead of ✜ ✜✜✜ 100s-1000s to ✜✜ Attempt to ✜✜ ✜ Verify Independently ✜✜ ✜✜ ✜ ✜✜✜ ✜✜ ✜✜✜✜ ✜Tuesday, November 1, 11
  35. 35. Thank YouTuesday, November 1, 11

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