Jillian M. Ketterer [email_address] October 13, 2009 What can we learn from sentiment analysis?
What is sentiment analysis? <ul><li>“… translating the vagaries of human emotion into hard data” [primarily in the online ...
 
In the virtual (online) world, organizations and individuals <ul><li>...have access to the universe of shared opinions </l...
Academic Research (e.g., not sure of purpose)
Personal Use
Market Research/Business Intelligence <ul><li>Marketing </li></ul><ul><li>Customer satisfaction </li></ul><ul><li>Predicti...
Powering Search Engines
Real-Time, Longitudinal Data Online Theoretically, this world exists.
Questions to Ponder <ul><li>What is the relationship between what you say online, and what you do (online and offline)? </...
(Pssst Google is getting sentimental) <ul><li>BANG!  Wow ‘em with a headline </li></ul>
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What can we learn from sentiment analysis?

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A short presentation about sentiment analysis from October 13, 2009. I will update the .ppt soon to make it flow better as a slideshow for reading as opposed to supplementing a presentation. I also have some references to add. I was just eager to add get something posted!

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What can we learn from sentiment analysis?

  1. 1. Jillian M. Ketterer [email_address] October 13, 2009 What can we learn from sentiment analysis?
  2. 2. What is sentiment analysis? <ul><li>“… translating the vagaries of human emotion into hard data” [primarily in the online world] </li></ul><ul><li>Mining the web for feelings, not facts (NYT) </li></ul><ul><li>“… us[ing] automated tools to discern, extract and process attitudinal information found in text…” </li></ul><ul><li>Sentiment Analysis: Opportunities and Challenges (Grimes, 2008) </li></ul><ul><li>“… an attempt to automatically process and possibly learn from the universe of people’s online chatter” </li></ul><ul><li> (Me, 2009) </li></ul>
  3. 4. In the virtual (online) world, organizations and individuals <ul><li>...have access to the universe of shared opinions </li></ul><ul><ul><ul><li>Reviews, comments, tweets, blog posts, tags </li></ul></ul></ul><ul><li>… as well as behavior(s) demonstrated by users </li></ul><ul><ul><ul><li>Clicks, purchases, browsing habits, social networking decisions (i.e. Share or not share? Follow or not follow?) </li></ul></ul></ul><ul><li>… over time, and often in real time, </li></ul><ul><ul><ul><li>Archive.org, Google/Twitter trends, RSS </li></ul></ul></ul><ul><li>… in a readily analyzable format. </li></ul>
  4. 5. Academic Research (e.g., not sure of purpose)
  5. 6. Personal Use
  6. 7. Market Research/Business Intelligence <ul><li>Marketing </li></ul><ul><li>Customer satisfaction </li></ul><ul><li>Prediction markets </li></ul><ul><li>Economics </li></ul><ul><li>Computational Linguistics </li></ul><ul><li>Semantic web (incorporating “feelings” into “meaning” – this could be big) </li></ul>
  7. 8. Powering Search Engines
  8. 9. Real-Time, Longitudinal Data Online Theoretically, this world exists.
  9. 10. Questions to Ponder <ul><li>What is the relationship between what you say online, and what you do (online and offline)? </li></ul><ul><li>What can be learned from data about “feelings”? </li></ul><ul><li>How do sentiments differ across domains? </li></ul><ul><li>Potential applications? </li></ul><ul><ul><ul><li>Scouting? </li></ul></ul></ul><ul><ul><ul><li>Reputation Management? </li></ul></ul></ul><ul><ul><ul><li>Evaluation/ Assessment? </li></ul></ul></ul>
  10. 11. (Pssst Google is getting sentimental) <ul><li>BANG! Wow ‘em with a headline </li></ul>

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