Data mining analytics investigate WeChat users’ behaviours: online social media and social commerce development

Abstract

Purpose As of December 2021, WeChat had more than 1.2 billion active users worldwide, making it the most active online social media in mainland China. The term social commerce is used to describe new online sales through a mix of social networks and/or peer-to-peer communication or marketing strategies in terms of allowing consumers to satisfy their shopping behaviour through online social media. Thus, given the numerous active users, the development of online social media and social commerce on WeChat is a critical issue of internet research. Design/methodology/approach This empirical study takes WeChat as the online social media research object. Questionnaires for WeChat users in China were designed and distributed. All items are designed as nominal and ordinal scales (not Likert scale). The obtained data was put into a relational database (N = 2,342), and different meaningful patterns and rules were examined through data mining analytics, including clustering analysis and association rules, to explore the role of WeChat in the development of online social media and social commerce. Findings Practical implications are presented according to the research findings of meaningful patterns and rules. In addition, alternatives to WeChat in terms of further development are also proposed according to the investigation findings of WeChat users’ behaviour and preferences in China. Originality/value This study concludes that online social media, such as WeChat, will be able to transcend the current development pattern of most online social media and make good use of investigating users’ behaviour and preferences, not only to stimulate the interaction of users in the social network, but also to create social commerce value in social sciences.