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Twitter Data Analytics

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Twitter Data Analytics

  1. 1. TWITTER DATA ANALYTICS
  2. 2. Twitter • Create and share ideas and information without barriers • Free social networking and micro-blogging site • Users sent 140 character long text messages
  3. 3. Facts about Twitter http://www.statisticbrain.com/twitter-statistics/
  4. 4. Online Communication, Offline Behavior slurs correlate with lower vote tallies for • Searches for ethnic minority politicians • Film title mentions correlate with revenue • Online expressions of public mood correlate with fluctuations in stock market prices • Sophisticated models for individual and group behavior
  5. 5. Twitter Can Predict US Elections • Fabio Rojas, Published on August 12, 2013, Indiana University professor from Department of Sociology • Digital democracy • “Modern politics happens when somebody comments on Twitter or links to a campaign through Facebook” • extracted 542,969 tweets • predicted the winner in 404 out of 435 competitive candidate for Congress in 2010 http://www.washingtonpost.com/opinions/how-twitter-can-predict-an-election/2013/08/11/35ef885a-0108-11e3-96a8d3b921c0924a_story.html?wpisrc=emailtoafriend
  6. 6. Kejriwal VS Modi on Social Media • “Arvind Kejriwal has better engagement on social media, Narendra Modi has twice the numbers” 15th Feb 2014 in Indian Express • • • • • Total number of followers Daily increase in followers Number of fake followers Tweets per day Topics http://indianexpress.com/article/india/politics/arvindkejriwal-narendramodi-social-media/
  7. 7. Why does this happen? • People talks +ve/-ve • all publicity is good publicity
  8. 8. More Tweets, More Votes • 537,231,508 tweets between Aug 1 to Nov 1, 2010 and 3,032,823,110 tweets between August 1 and November 5, 2012 • extracted 113,985 tweets in 2010 and 428,984 in 2012 that contain name of the Republican or Democratic candidate • 28,193 users in 2010 and 166,978 users in 2012 • For each candidate computed tweets that include their names DiGrazia J, McKelvey K, Bollen J, Rojas F (2013) More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior. PLoS ONE 8(11): e79449. doi:10.1371/journal.pone.0079449
  9. 9. Analysis • Ordinary Least Squares regression (OLS) to estimate the effect Twitter share on vote margin • Uses a bivariate model and a full model to estimate effect of the tweet and user share variables
  10. 10. Tweet Share • tws(i) : the amount of Twitter attention given to a particular candidate over their opposition in a particular race • i : district • twD(i) and twR(i) : Democratic and Republican frequencies
  11. 11. Figure 1. 2010 Republican Tweet Share vs. Vote Share. DiGrazia J, McKelvey K, Bollen J, Rojas F (2013) More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior. PLoS ONE 8(11): e79449. doi:10.1371/journal.pone.0079449 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079449
  12. 12. Figure 2. 2012 Republican Tweet Share vs. Vote Share. DiGrazia J, McKelvey K, Bollen J, Rojas F (2013) More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior. PLoS ONE 8(11): e79449. doi:10.1371/journal.pone.0079449 http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079449
  13. 13. Part of Tweet • Tweet (Unique identifier, the text of the tweet, tweet time, the username, case of retweets or mentions the account names of the other users associated with the tweet)
  14. 14. Part of Tweet • Emoticons : facial expressions pictorially represented using punctuation and letters • WATCH: #Malala witnesses the arrival of Syrian @refugees in Jordan in this moving video from #UNHCR http://uni.cf/1c35eyV • Target/Mention : Users of Twitter use the “@” symbol to refer to other users • Hashtags : Users usually use hashtags to mark topics
  15. 15. Acronyms • Acronym English expansion • • • • • • • gr8, gr8t lol rotf bff 4U Ab Gud Great Laughing out Loud Rolling on the floor Best Friend Forever For you About Good
  16. 16. Emoticons • Emoticon Polarity • • • • • :-) :) :o) :] :3 :c) :D C: :-( :( :c :[ D8 D; D= DX v.v :j Positive Extremely-Positive Negative Extremely-Negative Neutral
  17. 17. Register as a Developer • • • • https://dev.twitter.com/ Create API consumerKey and consumerSecret R Package - twitteR
  18. 18. Benefits • Social media analysis is cheap • Any citizen can harvest social media data and learn about the election in his or her area
  19. 19. References • http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal. pone.0079449#pone-0079449-t001 • http://josephdigrazia.com/site/Research.html • https://dev.twitter.com/ • http://en.wikipedia.org/wiki/Bivariate_analysis • http://indianexpress.com/article/india/politics/arvindkejriwalnarendramodi-social-media/ • http://www.washingtonpost.com/opinions/how-twitter-can-predictan-election/2013/08/11/35ef885a-0108-11e3-96a8d3b921c0924a_story.html?wpisrc=emailtoafriend
  20. 20. References • DiGrazia J, McKelvey K, Bollen J, Rojas F (2013) More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior. PLoS ONE 8(11): e79449. doi:10.1371/journal.pone.0079449 • http://www.statisticbrain.com/twitter-statistics/
  21. 21. •Thank you

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