Seth Grimes - Sentiment in Social Media


Published on

Published in: Technology, Business
1 Like
  • Be the first to comment

No Downloads
Total Views
On Slideshare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Seth Grimes - Sentiment in Social Media

  1. 1. Sentiment in Social Media: The Genie in the Bottle Seth Grimes Alta Plana Corporation 301-270-0795 -- -- @sethgrimes Monitoring Social Media – New York November 4, 2010
  2. 2. Sentiment in Social Media 3 Three assertions: 1.Human communications, online & off, are inherently subjective. 2.Online facts & opinions have business value. 3.Opinion often masquerades as Fact.
  3. 3. Sentiment in Social Media 4 Facts and Feelings The unemployment rate is 9.7%. Unemployment is WAY TOO HIGH!! The unemployment rate is higher than it was two years ago (5.1%). Former U.S. Federal Reserve Chairman Alan Greenspan said on Tuesday that the global recession will "surely be the longest and deepest" since the 1930s, adding that the Obama administration's Troubled Asset Relief Program will be insufficient to plug the yawning financial gap. [Reuters, Feb 18, 2009] [underlining added] Bernanke is doing a better job than Greenspan.
  4. 4. Sentiment in Social Media 7 Information access w/structure, sentiment: Sentiment+ Sentiment User intent?
  5. 5. Sentiment in Social Media 8 “In this example, you can quickly see that the Drooling Dog Bar B Q has gotten lots of positive reviews, and if you want to see what other people have said about the restaurant, clicking this result is a good choice.” -- “In the recap of [Searchology] from Google’s Matt Cutts, he tells us that: ‘If you sort by reviews, Google will perform sentiment analysis and highlight interesting comments.’ -- Bill Slawski, “Google's New Review Search Option and Sentiment Analysis,”
  6. 6. Sentiment in Social Media 10 We have a decision support need. We= Consumers Marketers Competitors Managers Decision support requires tools and techniques beyond general-purpose search/information access.
  7. 7. Sentiment in Social Media 11 Questions for business & government: What are people saying? What’s hot/trending? What are they saying about {topic|person|product} X? ... about X versus {topic|person|product} Y? How has opinion about X and Y evolved? How has opinion correlated with {our|competitors’|general} {news|marketing|sales|events}? What’s behind opinion, the root causes? • (How) Can we link opinions & transactions? • (How) Can we link opinion & intent? Who are opinion leaders? How does sentiment propagate across multiple channels?
  8. 8. Sentiment in Social Media 12 Counting term hits, in one source, at the doc level, doesn’t take you far... Good or bad? What’s behind the posts?
  9. 9. Sentiment in Social Media 13 “Sentiment analysis is the task of identifying positive and negative opinions, emotions, and evaluations.” -- Wilson, Wiebe & Hoffman, 2005, “Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis” Sentiment analysis turns attitudes into data. Ingredients: News. Social media. Enterprise feedback. Tools?
  10. 10. Rated negative?
  11. 11. ???
  12. 12. Sentiment in Social Media 17 Claim: You fall far short with (only) -- Doc-level analysis: • Need to look at features, opinion holders. Keyword-based analysis. • Need semantics. Human-only analysis. • Need the power of machines. Machine-only analysis. • Need the sensitivity of humans. “Reading from text in general is a hard problem, because it involves all of common sense knowledge.” -- Expert systems pioneer Edward A. Feigenbaum
  13. 13. Sentiment in Social Media 18 An accuracy aside: [WWH 2005] describes an inter-annotator agreement test. 10 documents w/ 447 subjective expressions. The two annotators agree on 82% of cases. Excluding of uncertain subjective expressions (18%) boosts agreement to 90%. (Wilson, Wiebe & Hoffman, 2005, “Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis”)
  14. 14. Sentiment in Social Media 19 Next slides have a few more examples. SAS Social Media Analytics. Clarabridge Social Media Analysis. Crimson Hexagon VoxTrot. Clarabridge sentiment analysis. A Jodange embeddable “gadget.”, a now defunct media portal from the Financial Times Group.
  15. 15. Sentiment in Social Media 24
  16. 16. Sentiment in Social Media 26 Beyond polarity: “We present a system that adds an emotional dimension to an activity that Internet users engage in frequently, search..” -- Sood & Vasserman & Hoffman, 2009, “ESSE: Exploring Mood on the Web”
  17. 17. Sentiment in Social Media 27 Happy Sad Angry Energetic Confused Aggravated Bouncy Crappy Angry Happy Crushed Bitchy Hyper Depressed Enraged Cheerful Distressed Infuriated Ecstatic Envious Irate Excited Gloomy Pissed off Jubilant Guilty Giddy Intimidated Giggly Jealous Lonely Rejected Sad Scared ----------------------- The three prominent mood groups that emerged from K-Means Clustering on the set of LiveJournal mood labels.
  18. 18. Sentiment in Social Media 28 Questions? Comments?
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.