Cascading Behavior in Yelp Reviews
Muhammad Raza Khan

TL;DR
This paper analyzes information cascades in Yelp reviews across various cities, revealing social influence patterns, cascade characteristics, and predictive features that can inform business strategies and consumer behavior analysis.
Contribution
It provides the first comprehensive analysis of Yelp review cascades, including topology enumeration, cross-city comparison, and the importance of non-root review features.
Findings
Significant presence of cascades in Yelp reviews
Heavy-tailed distribution of cascade sizes
Initial reviews can predict cascade size accurately
Abstract
Social media has changed the landscape of marketing and consumer research as the adoption and promotion of businesses is becoming more and more dependent on how the customers are interacting and feeling about the business on platforms like Facebook, Twitter, Yelp etc. Social review websites like Yelp have become an important source of information about different businesses. Social influence on these online platforms can result in individuals adopting or promoting ideas and actions resulting in information cascades. Research on information cascades have been gaining popularity over the last few years but most of the research has been focused on platforms like Twitter and Facebook. Research on the adoption or promotion of product using cascades can help determine important latent patterns of social influence. In this work, we have analyzed the spread of information i.e. cascades in Yelp…
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Taxonomy
TopicsComplex Network Analysis Techniques · Opinion Dynamics and Social Influence · Digital Marketing and Social Media
