Investigating the effects of textual reviews from consumers and critics on movie sales

The purpose of this paper is to investigate the sales impact of different types of online word-of-mouth based on their source (user vs critic) and form (structured vs unstructured).

The paper proposed a model by adopting the heuristic-systematic perspective of information processing and tested it using online movie reviews collected from Rotten Tomatoes. A unique dataset was constructed, which matched critic reviews and user reviews with metadata such as box-office sales and advertisement spending for 90 movies. Sentiment information from the textual contents of both user and critic reviews were text-mined and extracted. Data analyses were used to compare the box-office responsiveness of four types of reviews: user numeric ratings, user text reviews, critic numeric ratings and critic text reviews.

Critic reviews and user reviews influence sales through different forms: while user reviews impact sales through their aggregate numeric ratings, critic reviews exert their impact through textual narratives.

This study provides managerial implications to businesses on how to allocate their resources on different social media-related marketing strategies to maximize the economic value of online user-generated information.

The major contribution of this study is to extend the current understanding of the sales impact of online reviews to their textual aspect, as well as investigate how these textual narratives play different roles when offered by critics and users.