1 / 19

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?.

donald
Download Presentation

Sentiment Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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. Homework Assignment

More Related