LAUSR

Online game products have fueled the boom in China’s digital economy. Meanwhile, its public health concerns have sparked discussion among consumers on social media. However, past research has seldom studied the public health topics caused by online games from the perspective of consumer opinions. This paper attempts to identify consumers’ opinions on the health impact of online game products through non-structured text and large-size social media comments. Thus, we designed a natural language processing (NLP) framework based on machine learning, which consists of topic mining, multi-label classification, and sentimental analysis. The hierarchical clustering method-based topic mining procedure determines the compatibility of this study and previous research. Every three topics are identified in “Personal Health Effects” and “Social Health Effects”, respectively. Then, the multi-label classification model’s results show that 61.62% of 327,505 comments have opinions about the health effects of online games. Topics “Adolescent Education” and “Commercial Morality” occupy the top two places of consumer attention. More than 31% of comments support two or more topics, and the “Adolescent Education” and “Commercial Morality” combination also have the highest co-occurrence. Finally, consumers expressed different emotional preferences for different topics, with an average of 63% of comments expressing negative emotions related to the health attributes of online games. In general, Chinese consumers are most concerned with adolescent education issues and hold the strongest negative emotion towards the commercial morality problems of enterprises. The significance of research results is that it reminds online game-related enterprises to pay attention to the potential harm to public health while bringing about additional profits through online game products. Furthermore, negative consumer emotions may cause damage to brand image, business reputation, and the sustainable development of the enterprises themselves. It also provides the government supervision departments with an advanced analysis method reference for more effective administration to protect public health and promote the development of the digital economy.