Characteristics of Chinese Online Movie Reviews and Opinion Leadership Identification

This article uses a case study of the reception of popular South Korean films in China to investigate aspects of proactive participation in the Chinese social mediasphere. Based on the big data collected from the popular Douban online review platform, the authors provide an in-depth investigation of the characteristics of online opinion leaders and leadership. First, we statistically analyze user-generated content-related features for both leader and non-leader groups. In addition, we employ a Bayesian optimization-based imbalanced learning algorithm to identify characteristics of the minority opinion leaders. The efficiency of the proposed algorithm is evaluated based on 17,786 reviews collected from 35 popular films covering a variety of genres, and the proposed algorithm is shown to perform accurately by identifying opinion leaders, compared to other state-of- the-art approaches. Our study also reveals some major features associated with opinion leaders, such as vocabulary, viewing habits, and friendship networks. Finally, we show how these elements are contributing to new understandings of the rapidly transforming digital domain of Chinese social media and the roles of such platforms.