With the emergence of online communities, more and more people are participating in online technology communities to meet personalized learning needs. This study aims to investigate whether and how male and female users behave differently in online technology communities. Using text data from the Python Technology Community, through the LDA (Latent Dirichlet Allocation) model, sentiment analysis, and regression analysis, this paper reveals the different topics of male and female users in the online technology community, their sentimental tendencies and activity under different topics, and their correlation and mutual influence. The results show the following: (1) Male users tend to provide information help, while female users prefer to participate in the topic of making friends and advertising. (2) When communicating in the technology community, male and female users mostly express positive emotions, but female users express positive emotions more frequently. (3) Different emotional tendencies of male and female users under different topics have different effects on their activity in the community. The activity of female users is more susceptible to emotional orientation.

This article analyzes the different effects of industrial aggregation, industry-university collaboration, foreign direct investment and government support on innovation performance and the synergistic effect between them, thereby to identify the determinants of innovation output of Chinese high-tech industry in the period 2009-2018. The results indicate that industrial agglomeration and industry-university collaboration both have a significant positive impact on the patent output of hightech industries, but the synergistic effect between industrial agglomeration and industry-university collaboration is significantly negative. Meanwhile, both of foreign direct investment and government support could negatively affect the innovation output, while their synergistic effect is positive. INDEX TERMS Industrial agglomeration; University-industry collaboration; Patent output; High-tech industry; Open innovation.

With the prevalence of the Internet and new media channels, consumer reviews have become one of the main determinants of Consumers’ purchasing decisions. This paper uses the Latent Dirichlet Allocation (LDA) model to identify the key factors that are of major concern to consumers, including design factors, laptop setup factors, logistics factors, after-sales factors, and user experience factors. And, we classify these factors into product quality factors and supporting service factors for new products. We then explore the relationship between online reviews and purchase decisions under these different factors, and also further explore the impact of interactions between online review metrics on purchase decisions. Our findings suggest that the impact of online reviews on consumer purchase decisions also varies considerably across different consumer focus factors. In addition, we find that the impact of the interaction between online review features is complex. In particular, consumers do not follow the positive guidance and make purchase decisions as we would expect when confronted with a large number of positive emotional polarity online reviews. Meanwhile, the interaction between negative emotional polarity and variance of online reviews had no significant effect on consumer purchase decisions. The variance of online reviews has a limited role in reducing consumer risk perceptions triggered by negative emotional polarity. Our study provides new evidence for the study of the impact of online reviews through text mining.

Community commitment is the key to the success of virtual communities. Under the background of virtual knowledge community, based on motivation hierarchy model and integrated emotion theory, this paper takes “motivation-emotion-community commitment” as the main framework, and introduces multiple mediation and regulation functions to establish the relationship model of motivation hierarchy, integrated emotions, and community commitment. The results show that the user motivation follows the hierarchical structure of the layer-by-layer influence from the situational level to the personality level, that is, knowledge-seeking motivation and entertainment-seeking motivation at a situational level will positively affect social- interaction motivation at the contextual level, thereby enhancing user self-efficacy at personality level. Users have abundant integrated emotions toward the virtual knowledge community, namely, satisfaction, attachment, and identity, and such multi-integrated emotional model is more conducive for promoting community commitment of users. At the same time, attachment, identity, and satisfaction have an interactive complement, that is, when satisfaction is low, attachment and identity will complement and strengthen community commitment.

China's automotive industry has entered a stage of great growth. Owing to the widespread and rapid information dissemination of online automotive forums, they have become an important source for manufacturers to collect product defect information and understand consumer preferences. The purpose of this study is to investigate car defect information and consumer preferences from online automotive forums and segment consumers based on consumer preferences, which holds great promise as a means for companies to improve product design and consumer relationship management. Based on text data of China's top‐ranked Pacific Auto Network, we applied the LDA model, sentiment analysis, text classification, and cluster analysis methods to determine the influencing factors of automobile consumers’ purchasing behavior, identified automobile product defects, and subdivided consumer groups. The results show that the factors affecting consumers’ car buying behavior are low fuel consumption, affordable price, superior performance, fashionable appearance, and comfortable use. Car product defects are mainly reflected in the three aspects of the car's performance, comfort, and configuration; there are six kinds of consumer groups: price seekers, fuel consumption seekers, performance seekers, comfort seekers, cost performance seekers, and appearance seekers. Of these, cost performance seekers make up the largest proportion, and they constitute the largest group of intention purchasers. These findings can help enterprises develop targeted product improvement programs, but also provide a decision‐making basis for enterprises to achieve precision marketing.