Whose and What Chatter Matters? The Impact of Tweets on Movie Sales

Abstract

Social broadcasting networks like Twitter in the U.S. and “Weibo” in China are transforming the way online word-of-mouth is disseminated and consumed in our society. We investigate whether and how Twitter WOM affects movie sales using publicly available Twitter data and common text mining algorithms. We find that more Twitter WOM messages always leads to more movie sales, however, the magnitude of the impact crucially depends of whom the WOM messages are from and what the WOM messages are about. Measuring Twitter users’ influence by their number of followers, we find that WOM messages from a more influential person is significantly larger than WOM messages from a less influential person. In support to some recent findings that valence does matter to the impact of WOM on product sales, we also find that the impact of positive Twitter WOM is larger than negative WOM. However, the most powerful Twitter WOM are those tweets where the authors express their intention to watch a certain movie. We attribute this to the dual effects of intention tweets on movie sales: the direct effect on movie sales through the WOM author’s own purchase behavior, and the indirect effect on movie sales through either the awareness effect or the persuasive effect of the WOM on its recipients. These findings provide different perspectives of understanding WOM compared with earlier literature and have important managerial implications.

Keywords: Twitter, word-of-mouth, dynamic panel data

JEL Classification: M3, C2