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Sentiment Analysis

Sentiment Analysis. Applied Advertising & Public Relations Research JOMC 279. "Listening is the study of naturally occurring conversations, behaviors, and signals—information that may or may not be guided—that brings the voice of people's lives in to a brand.". Why Do Brands Listen?.

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Sentiment Analysis

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  1. Sentiment Analysis Applied Advertising & Public Relations Research JOMC 279

  2. "Listening is the study of naturally occurring conversations, behaviors, and signals—information that may or may not be guided—that brings the voice of people's lives in to a brand."

  3. Why Do Brands Listen? • Insights (wants, unmet needs, challenges) • Voice of consumer • Redefine relationships • Understand shifts in perspectives • Understand context & reasons why

  4. Where Do Brands Listen? • Offline • Comment cards • Trade-show notes • CRM / sales mgmt. systems • Online • Brand backyard • Customer backyard

  5. Whom Do Brands Listen To? • Customers • Prospects • Business partners • Friends, contacts, followers • Others

  6. How Do Brands Make Senseof What They Hear? • Search & Monitoring • Text Analytics • Full-Service Listening Platforms • Private Communities

  7. Measuring whatyour customers say about youwhen they're talking to each other. LISTENING

  8. Advantages (Online) • Unobtrusiveness • Immediate / Real-time • Natural, rich, unfiltered WOM • BIG data

  9. Disadvantages (Online) • Ethics • Representativeness / Accuracy • WOM Noise • BIG data

  10. Sentiment Analysis • aka “opinion mining” • Measurement of emotion in texts • Polarity • Strength • Human coding vs. NLP • Methodological standards / transparency

  11. Project 2 Results • Data set: You were provided with 200 Tweets related to pizza.  (2 sets) • Code each Tweet as • Positive, Negative, Mixed, or Neutral. • When coded as Positive, Negative, or Mixed, identify the portion of the Tweet that resulted in that decision. • Evaluate the difficulty of the coding decision.

  12. Natural Language Processing • SocialRadar vs. SentiStrength • Observed agreement = .315 • Both data sets • Why would computing kappa be inappropriate in this situation?

  13. “After coding these tweets, it is easy to see why computers might not be the most effective way for a brand or company to decipher customers’ tweets about a product or service.”

  14. “I have come to admire people who are professional coders.”But are humans better?

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