Restaurant online reviews and their manipulations

My thesis contains two separate chapters. In the first chapter, I focus on what consumers express about their dining experience. I present a case study using Yelp restaurant review data on what affects restaurant customers' sentiment responses to dining out. The case study uses a sentiment-analysis method to extract and generate sentiment indices from 175,879 text-based Yelp restaurant reviews. I then examine the relationships between our sentiment indices and ratings and what factors(food, service, expenditure, and social) affect consumer dining experience more than others. In the second chapter, I find that, other than seller manufactured fake reviews, review platforms can also manipulate reviews by changing consumers' leaving review behaviours. Online review platforms are able to attract more satisfied consumers to leave reviews which results in rating inflation in their platforms. In this situation, even if all the reviews are real, consumers still receive biased information from online reviews. My paper provides empirical evidence for information design theory.masters, M.S., Agricultural Economics and Rural Sociology (Applied Economics) -- University of Idaho - College of Graduate Studies, 2020-0