In online communities, such as Twitter, Facebook, or Reddit, millions of pieces of contents are generated by users every day, and these user-generated contents show a great variety of topics discussed that make the online community vivid and attractive. However, the reasons why UGCs show great variety and how a firm can influence this variety was unknown, which had been an obstacle to understanding and managing UGCs’ variety. This study fills these two gaps based on variety-seeking theory and topic modeling, (...) which is a technique in machine learning. We extract, quantitatively, the topic of the UGCs using topic modeling and divide UGCs into two types: single topic and multiple topics. The user’s tendency to choose the type of UGC is used to measure variety-seeking behavior. We found that users have an intrinsic preference for variety when producing UGCs; the more single topic UGCs were produced in the past, the higher the probability of producing multiple topics UGC and the lower the probability of producing single topic UGC would be in the next, and vice versa. Furthermore, we discussed the effect of language/linguistic style matching between firm feedbacks and UGCs on users’ variety-seeking tendencies in UGCs’ production. This study makes three contributions: broadening variety-seeking theory to new behavior, that is content production behavior, and the results demonstrated that people would show a variety-seeking behavior in producing UGCs. a new feasible method to measure the variety of UGCs by using topic modeling to extract the topics of UGCs and then measure the variety-seeking behavior in producing UGCs by analyzing the choice between single topic and multiple topics. guidance for the firm to alter LSM of feedbacks to influence the variety of UGCs. (shrink)

Some previous studies have explored the impact of family function on school belonging. However, little is known about the parallel mediating relationship underlying them. This study aims to investigate the formation mechanism of school beginning in a sample of Chinese adolescents and examined the parallel mediating role of interpersonal self-support and individual self-support in the link between family function and school belonging. A cross-sectional study was conducted in four schools of the district of Hunan province in China, and 741 students (...) were surveyed using cluster sampling. Family cohesion and adaptability scale, Adolescent students self-supporting personality scale, School belonging scale were applied. The results indicated that interpersonal self-support and individual self-support, together, and uniquely, parallel mediated the relationship between family function and school belonging. It can be concluded that family function not only has direct effects on school belonging but also has indirect effects through interpersonal self-support and individual self-support. (shrink)

This paper investigates a composite learning prescribed performance control scheme for uncertain strict-feedback system. Firstly, a prescribed performance boundary condition is developed for the tracking error, and the original system is transformed into an equivalent one by using a transformation function. In order to ensure that the tracking error satisfies the PPB, a sufficient condition is given. Then, a control scheme of PPC combined with neural network and backstepping technique is proposed. However, the unknown functions cannot be guaranteed to estimate (...) accurately by this method. To solve this problem, predictive errors are defined by applying online recorded date and instantaneous date. Furthermore, novel composite learning laws are proposed to update NN weights based on a partial persistent excitation condition. Subsequently, the stability of the closed-loop system is guaranteed and all signals are kept bounded by using composite learning PPC method. Finally, simulation results verify the effectiveness of the proposed methods. (shrink)