Online word-of-mouth as a predictor of television rating

Abstract

Purpose

Despite the growing importance of online word-of-mouth (WOM) with regard to television (TV) ratings, it is usually excluded from early prediction models. The purpose of this paper is to investigate the role of online WOM in TV ratings predictions, focussing on whether the incorporation of online WOM could improve predictions of TV ratings, and extracts meaningful rules for decision-making.

Design/methodology/approach

The author uses online WOM as a potential predictive variable in the TV ratings prediction model. The author matches a list of programs based on TV ratings for the movie channel with internet user reviews and TV ratings information from Yahoo! Movies (YM) and XYZ Company. The data set includes 71 movies, for which the data were analyzed with a hybrid model.

Findings

Grey relational analysis shows that online WOM is a useful ex ante determinant of TV ratings. As a predictive variable, it plays an essential role in enhancing TV ratings predictions. The experimental results also indicate that the proposed model surpasses other listed methods in terms of both accuracy and reduction of variables, while the proposed procedure yields a set of easily understandable decision rules that facilitate the interpretation of TV ratings information.

Practical implications

This paper identifies critical predictors of TV ratings and suggests that online WOM messages are a credible source. A hybrid model is developed to illustrate an intelligent prediction system for TV ratings.

Originality/value

The study demonstrates the effectiveness of online WOM and its impact on TV ratings. It offers an intelligent prediction system for TV ratings with practical implications for managers within the TV industry.

Citation

Yeh, C.-C. (2015), "Online word-of-mouth as a predictor of television rating", Online Information Review, Vol. 39 No. 6, pp. 831-847. https://doi.org/10.1108/OIR-01-2015-0033