This is a past event.
The campus community is invited to hear Junhong "Jun" Min, professor of marketing in the Michigan Tech College of Business, and Matthew Monte, president of Monte Consulting, present 'Strategic Use of the Inconsistency between Online Ratings and Reviews: An Application of Sentimental Analysis in Marketing' as part of the College of Business Brown Bag Research Seminar Series, from noon to 1 p.m. on Wednesday, December 8, in the Academic Office Building, Room 101.
From the abstract:
Online ratings and reviews provide marketing managers with the quality indicator that makes it possible to capture consumers' attitudes and behavioral information and thus to create customer value in the age of digitalization. However, the authors argue that customer insights developed only based on online ratings could result in a conundrum, particularly if inconsistency between online ratings and reviews is discounted. This research aims to tackle the problem by first offering a theoretical explanation of why consumers' ratings and reviews are not necessarily consistent. Later, using the 12,500 ratings and reviews collected from the Internet Movie Database (IMDb.com), the authors identified the factors causing the inconsistency between online ratings and reviews. Results showed that about 32 percent of online ratings were inconsistent with consumers' review comments. The inconsistency was caused by the sentiment valence (positive vs. negative), the text length (short vs. long), and the rating distribution (extreme vs. middle). Surprisingly, the sample size (small vs. large) was not statistically significant. The authors propose an innovative research method using sentiment analysis and discuss the strategic use of the online rating and review inconsistency in the marketing field.
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