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The purpose of this paper is to construct a multi-relational network for an online sharing platform in the age of the sharing economy, to identify the factors impacting users’ product adoption behavior and to predict consumers’ purchases of user-generated products on the platform.

The study conducted multi-relational network analyses of five different sub-networks in identifying influential factors for e-book adoption. Meanwhile, the study adopted machine learning methods with different classification algorithms and feature sets to predict users’ purchasing behaviors.

The authors found that an individual’s adoption of a product was correlated with his or her purchasing habits and collaboration with others on the online sharing platform. Through the inclusion of network features, the authors were able to build a predictive model that forecasted consumers’ purchases of user-generated e-books with reasonable accuracy.

The interdisciplinary approach used in the study can serve as a good reference for identifying factors impacting the product adoption behavior of users in the online sharing platform, through employing different sociological and computational methods.

The outcome of the study has provided important managerial implications, especially for the design of social commerce platform in the age of the sharing economy.

The authors verified the social influence impacting consumers’ product adoption behavior and shed light on the value of collaboration in the age of the sharing economy.

The study was the first to identify user-generated e-book adoption on an online sharing platform from a multi-relational network perspective. The idea and the approach supplied a new method of behavioral analysis in the context of a sharing economy.

The purpose of this study is to solve the problems caused by the growing volumes of pre-annotated literature and variety-oriented annotations, including teamwork, quality control and time effort.

An annotation collaboration workbench is developed, which is named as Bureau for Rapid Annotation Tool (Brat). Main functionalities include an enhanced semantic constraint system, Vim-like shortcut keys, an annotation filter and a graph-visualizing annotation browser. With these functionalities, the annotators are encouraged to question their initial mindset, inspect conflicts and gain agreement from their peers.

The collaborative patterns can indeed be leveraged to structure properly every annotator’s behaviors. The Brat workbench can actually be seen as an experienced-based annotation tool by harnessing collective intelligence. Compared to previous counterparts, about one-third of time can be saved on Xinhuanet military news and patent corpora with the workbench.

The various annotations are very popular in real-world annotation tasks with multiple annotators. Though, it is still under-discussed on variety-oriented annotations. The findings of this study provide the practitioners valuable insight into how to govern annotation projects. In addition, the Brat workbench takes the first step for future research on annotating large-scale text resources.

This study aims to conduct a dynamic analysis of consumer attitudes towards domestic brands under the influence of multiple-period opinion events, providing methodological guidance for the overall development of fast-fashion clothing brands.

This study takes the Xinjiang cotton event and ERKE donation event in 2021 as the samples and Weibo comments on the hot topic of the fact that ANTA’s total turnover exceeded NIKE’s on the 2021 Double 11 as the first and explores the process and influencing factors of consumer domestic brand attitude change through latent Dirichlet allocation (LDA) model.

Under the influence of multiple public opinion events, consumers’ attitudes towards domestic brands experienced changes from brand awareness and brand identification to brand loyalty. First of all, patriotism and the awareness of Chinese goods lead to consumers’ brand awareness. The social responsibility and perceived quality of the later stage will stimulate consumers’ brand identification. Finally, the matching of national pride and perceived products will promote consumers’ brand loyalty.

This study establishes a model of the evolution of consumer attitudes towards domestic brands, revealing for the first time from a dynamic perspective the factors influencing these attitudes. This study offers a novel perspective on the processes and structures of the relationship between consumers and domestic brands.