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HOW NOT To predict ELECTIONS

HOW NOT To predict ELECTIONS. Panagiotis T. Metaxas CS, Wellesley College & CRCS, Harvard University Joint work with Eni Mustafaraj and Dani Gayo-Avello. Overview. Social Media can “ predict the present/future ” Success stories Electoral Predictions with Social Media

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HOW NOT To predict ELECTIONS

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  1. HOW NOT To predict ELECTIONS Panagiotis T. Metaxas CS, Wellesley College & CRCS, Harvard University Joint work with Eni Mustafaraj and Dani Gayo-Avello

  2. Overview • Social Media can “predict the present/future” • Success stories • Electoral Predictions with Social Media • Successful Predictions • Can Twitter predict US Elections? • Elsewhere: Can Google Trends predict US Elections? • How To Predict Elections using Social Media

  3. Social Media can “predict the future” (?!)

  4. To Predict (according to Merriam-Webster)

  5. Successful Electoral Predictions • This slide was intentionally left blank

  6. Successful Would-be Predictions • Methods Used: • Raw volume of Tweets • Sentiment Analysis of Tweets • Data Used: • 2009 German Elections Tweets • 2008 US Presidential Elections Tweets • Our Data: • 2010 Special Senatorial Elections (MA) Tweets • 2010 Senatorial Elections (CO, NV, CA, KY, DE) Tweets

  7. Can Twitter Volume Predict? • Twitter volume (would have) predicted correctly 50% of the high-visibility US Congressional races

  8. Can Tweet Sentiment Predict? • Sentiment analysis (would have) predicted correctly 50% of the high-visibility US Congressional races • But was it sensing the sentiment correctly?

  9. “What if you had used some other methods?” • We did not invent the methods we used,we just evaluated them on data other than those they were designed for • We started off expecting to predict successfully(In fact, we were “predicting” at times ;-) • But we learned a lot from these experiments:How to Predict Using Social Media

  10. How To Predict • A method of prediction should be an algorithmfinalized before the elections: • (input) how Social Media data are to be collected, including the dates of data collection, • (filter) the way in which the cleanup of the data is to be performed (e.g., the selection of keywords relevant to the election), • (method) the algorithms to be applied on the data along with their input parameters, and • (output) the semantics under which the results are to be interpreted.

  11. How To Predict • A method of prediction should be an algorithm. • Data from Social Media are fundamentally different than Data from Natural Phenomena. • People will change their behavior the next time around • Spammers & Activists will try to take advantagee.g. “Twitter Bomb” and “Prefab Tweeter Factory”

  12. How To Predict • A method of prediction should be an algorithm. • Data from Social Media are fundamentally different than Data from Natural Phenomena. • Form a testable theory on why and when it predicts. • Go past the OMG! Factor • Avoid the self-deception syndrome

  13. How To Predict • A method of prediction should be an algorithm. • Data from Social Media are fundamentally different than Data from Natural Phenomena. • Form a testable theory on why and when it predicts. • (maybe) Learn from the professional pollsters. • Tweet ≠ User • User ≠ Eligible Voter • Eligible Voter ≠ Voter

  14. Thank you!

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