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Today, individuals use social media to express their opinions and feelings, which offers a living laboratory to researchers in various fields, such as management, innovation, technology development, environment and marketing. It is therefore necessary to understand how the language used in user-generated content and the emotions conveyed by the content affect responses from other social media users.

In this study, almost 700,000 posts from Twitter (as well as Facebook, Instagram and forums in the appendix) are used to test a conceptual model grounded in signaling theory to explain how the language of user-generated content on social media influences how other users respond to that communication.

Extending developments in linguistics, this study shows that users react negatively to content that uses self-inclusive language. This study also shows how emotional content characteristics moderate this relationship. The additional information provided indicates that while most of the findings are replicated, some results differ across social media platforms, which deserves users' attention.

This article extends research on Internet behavior and social media use by providing insights into how the relationship between self-inclusive language and emotions affects user responses to user-generated content. Furthermore, this study provides actionable guidance for researchers interested in capturing phenomena through the social media landscape.

The purpose of this study is to present an analysis of the Islamic good governance concept and means known as Al-Siyasah Al-Syar’iyyah as a principle and approach for combating corruption. This literature review aims to synthesize extant literature that discusses the determinants of integrity and how to prevent and combat corruption based on the Al-Siyasah Al-Syar’iyyah perspective.

A systematic search was conducted on a literature review based on Scopus and referred journals from Google Scholar databases. A manual search on Google Scholar was performed to identify additional relevant studies. Studies were selected based on the predetermined criteria. They were thematically examined using content analysis.

The study found that most of the 45 works of the literature, (41 studies and four chapters) suggested that corruption should be considered a sin and that education of Al-Siyasah Al-Syar’iyyah’s perspective against corruption, emphasizing the principle of piety, the institutionalization of justice and accountability, good governance performance with an emphasis on its belief in self-accountability and justice, is the means to combat corruption.

This study is unique in that it focuses on locating material on battling corruption from the standpoint of Al-Siyasah Al-Syar’iyyah. Based on the al-Quran, the Sunnah and the best practices of Muslim rulership, this notion provides an epistemological, ethical and ontological stance in Islam.

The purpose of this paper was (1) to examine the underexplored intersection of sports betting and favorite team loyalty, and (2) to assess differences in gambling behavior among sport bettors by varying levels of team loyalty.

A total of 1,555 National Football League (NFL) bettors and non-betting NFL fans were surveyed to assess media consumption across a mix of team loyalty attitudes and betting behaviors.

Statistically significant differences were found between four types of NFL fans (casual, team loyalty-dominant, betting-dominant and hybrid) as it relates to media consumption in various forms. Most notably, the results suggested symbiosis between the activities.

The symbiosis finding, though preliminary, suggests the activity provides an additional platform for consumers to connect with spectator sport. Furthermore, the act of betting, like participation in fantasy sports, appears to spur consumption of the NFL product generally. The study, however, was limited to NFL fans, did not specify the method for sports betting, nor the intensity of gambling.

Teams should not worry that betting detracts from fan engagement with the team product. Also, leagues and media providers should continue to highlight betting content as participants consume at higher rates than non-participating sports fans.

Team fandom may potentially moderate problem behavior among bettors. The betting results indicate being a loyal team fan lowers one’s gambling spend per month and largest bet compared to non-loyal bettors. However, the hybrid fan showed significantly higher media consumption levels.

Sports fans have more opportunities to interact and engage with their favorite games than ever before. However, consumers have limited amounts of time and money, and this study is one of the first to examine differences in fan interests and behaviors related to sport betting and team loyalty and the resulting viewership and consumption behavior.

The purpose of this study is to investigate consumers' emotional responses to artificial intelligence (AI) defeating people. Meanwhile, the authors investigate the negative spillover effect of AI defeating people on consumers' attitudes toward AI companies. The authors also try to alleviate this spillover effect.

Using four studies to test the hypotheses. In Study 1, the authors use the fine-tuned Bidirectional Encoder Representations from the Transformers algorithm to run a sentiment analysis to investigate how AI defeating people influences consumers' emotions. In Studies 2 to 4, the authors test the effect of AI defeating people on consumers' attitudes, the mediating effect of negative emotions and the moderating effect of different intentions.

The authors find that AI defeating people increases consumers' negative emotions. In terms of downstream consequences, AI defeating people induces a spillover effect on consumers' unfavorable attitudes toward AI companies. Emphasizing the intention of helping people can effectively mitigate this negative spillover effect.

The authors' findings remind governments, policymakers and AI companies to pay attention to the negative effect of AI defeating people and take reasonable steps to alleviate this negative effect. The authors help consumers rationally understand this phenomenon and correctly control and reduce unnecessary negative emotions in the AI era.

This paper is the first study to examine the adverse effects of AI defeating humans. The authors contribute to research on the dark side of AI, the outcomes of competition matches and the method to analyze emotions in user-generated content (UGC).