A Text Mining Approach for Sustainable Performance in the Film Industry

Many previous studies have shown that the volume or valence of electronic word of mouth (eWOM) has a sustainable and significant impact on box office performance. Traditional studies used quantitative data, such as ratings, to measure eWOM. However, recent studies analyzed unstructured data, such as comments, through web-based text analysis. Based on recent research trends, we analyzed not only quantitative data, like ratings, but also text data, like reviews, and we performed a sentiment analysis using a text mining technique. Studies have also examined the effect of cultural differences on the decision-making processes of individuals and organizations. We applied Hofstede’s cultural theory to eWOM and analyzed the moderating effect of cultural differences on eWOM influence. We selected 338 films released between 2006 and 2015 from the BoxOfficeMojo database. We collected ratings and reviews, box office revenues, and other basic information from the Internet Movie Database (IMDb). We also analyzed the effects of cultural differences, such as power distance, individualism, uncertainty avoidance, and masculinity, on box office performance. We found that user comments have a greater impact on film sales than user ratings, and movie stars and co-production contribute to box office success. We also conclude that cultural and geographical differences moderate the sentiment elasticity of eWOM.