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Health misinformation on social media threatens public health. A critical question that sheds light on the propagation of health misinformation across social media platforms revolves around identifying the specific types of social media users susceptible to this issue. This study provides an initial insight into this matter by examining the underlying psychological mechanism that renders users susceptible to health misinformation.

In this study, we developed an integrated model of susceptibility to health misinformation, drawing on the motivation-opportunity-ability theory and the elaboration likelihood model. We collected the data from a sample of 342 social media users in China. Furthermore, the fuzzy-set qualitative comparative analysis was adopted to examine the proposed model and uncover the causal recipes associated with susceptibility to health misinformation.

The results indicated that there are three configural types of users that are susceptible to health misinformation: the health-consciousness core-driven type, the popularity-driven core type and the dual-driven type characterized by both high health consciousness and information popularity. Among these, high health-consciousness and the reliance on information popularity-based pathways emerge as pivotal factors influencing susceptibility to health misinformation.

This study contributes to the social media literature by identifying various psychological traits that lead to social media users’ susceptibility to health misinformation. Additionally, the study provides comprehensive guidance on how to mitigate the spread of health misinformation.

Sharing and disseminating debunking information are critical to correcting rumours and controlling disease when dealing with public health crises. This study investigates the factors that influence social media users' debunking information sharing behaviour from the perspective of persuasion. The authors examined the effects of argument adequacy, emotional polarity, and debunker's identity on debunking information sharing behaviour and investigated the moderating effects of rumour content and target.

The model was tested using 150 COVID-19-related rumours and 2,349 original debunking posts on Sina Weibo.

First, debunking information that contains adequate arguments is more likely to be reposted only when the uncertainty of the rumour content is high. Second, using neutral sentiment as a reference, debunking information containing negative sentiment is shared more often regardless of whether the government is the rumour target, and information containing positive sentiment is more likely to be shared only when the rumour target is the government. Finally, debunking information published by government-type accounts is reposted more often and is enhanced when the rumour target is the government.

The study provides a systematic framework for analysing the behaviour of sharing debunking information among social media users. Specifically, it expands the understanding of the factors that influence debunking information sharing behaviour by examining the effects of persuasive cues on debunking information sharing behaviour and the heterogeneity of these effects across various rumour contexts.

Talent is a key resource for urban development, and building and disseminating urban brands have an important impact on attracting talent. This paper explores what kind of urban brand ecology (UBE) can effectively enhance urban talent attraction (UTA). We explore this question using a novel grey quantitative configuration analysis (GQCA) model.

To develop the GQCA model, grey clustering is combined with qualitative configuration analysis (QCA). We conducted comparative configuration analysis of UTA using fuzzy set QCA (fsQCA) and the proposed GQCA.

We find that the empirical results of fsQCA may contradict the facts, and that the proposed GQCA effectively solves this problem.

Based on the theory of UBE, we identify bottleneck factors for improving UTA at different stages. Seven configuration paths are described for cities to enhance UTA. Theoretically, this study expands the application boundaries of UBE.

The proposed GQCA effectively solves the problem of inconsistent analysis and facts caused by the use of a binary threshold by the fsQCA. In practical case studies, the GQCA significantly improves the reliability of configuration comparisons and the sensitivity of QCA to cases, demonstrating excellent research performance.

Academic conferences play a crucial role in fostering scholarly exchanges and discussions among core members, thereby shaping the core performance of these events. Understanding the contributions of scholars in academic conferences is essential for advancing the goals and development of such events. This paper aims to discuss the aforementioned idea.

This paper proposes a comprehensive measurement method for measuring scholars' academic activeness in academic conferences. Based on the essence of academic activeness, a measurement model is constructed, comprising the breadth of academic activeness using the RFM model and the depth of academic activeness using the ATM model. Additionally, effective categories of scholars are derived from the model, facilitating the identification of valuable scholars in academic conferences.

Empirical evidence from ASIS&T conference records over the past 20 years demonstrates that the proposed measurement indicators have better coverage compared to traditional evaluation indicators, thus complementing existing scholar evaluation indictators. Furthermore, the academic activeness measurement model presented in this paper exhibits good efficacy in identifying important value and active scholars.

This paper pays attention to the activeness of scholars in academic conferences. It broadens the evaluation of academic conferences and scholars and supplements the evaluation indicators of academic influence.