Listening to the Consumer: Exploring Review Topics on Airbnb and Their Impact on Listing Performance

While research has investigated various aspects of electronic word of mouth and their effects on business performance, it has neglected detailed topics in reviews. This study explores this new aspect in reviews and examines the effects of review topics on Airbnb listing performance. We use 2,799,420 reviews from 64,464 listings posted on the Airbnb platform in 10 U.S. cities. Using the latent Dirichlet allocation method, we identify 16 key topics of consumer reviews on Airbnb. Then, using a negative binomial regression model, we show that various factors can affect a listing's performance on Airbnb. These findings have implications for Airbnb hosts and the sharing economy.