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

Abstract

Social broadcasting networks such as Twitter in the U.S. and \Weibo" in China are transforming the way online word-of-mouth (WOM) is disseminated and consumed in the digital age. We investigate whether and how Twitter WOM aects movie sales by estimating a dynamic panel data model using publicly available data and well known machine learning algorithms. We nd that chatter on Twitter does matter, however, the magnitude and direction of the eect depends on whom the WOM is from and what the WOM is about. Measuring Twitter users' in uence by how many followers they have, we nd that the eect of WOM from more in uential users is signicantly larger than that from less in uential users. In support of some recent ndings about the importance of WOM valence on product sales, we also nd that positive Twitter WOM increases movie sales while negative WOM decreases them. Interestingly, we nd that the strongest eect on movie sales comes from those tweets where the authors express their intention to watch a certain movie. We attribute this to the dual eects of such intention tweets on movie sales: the direct eect through the WOM author's own purchase behavior, and the indirect eect through either the awareness eect or the persuasive eect of the WOM on its recipients. Our ndings provide new perspectives to understand the eect of WOM on product sales and have important managerial implications. For example, our study reveals the potential values of monitoring people's intention and sentiment on Twitter and identifying in uential users for companies wishing to harness the power of social broadcasting networks.