Sports-related online abuse has evolved into an inevitable issue and even those athletes and teams honored as national icons cannot be exceptional. This study explores how exposure to abusive content on social media affects sports fans’ behavior. More specifically, the researchers draw from social psychology and exam the rejection-identification model with fans’ team identity and hate for rival teams as parallel competitive mediators in the context of online abuse in sports. Using a sample comprising 917 fans of the Chinese Women’s National Volleyball Team (CWV), the study suggested that exposure to online abuse is linked to a decrease in fans’ intention to create content and advocate for their teams on social media. However, the identification with their idol and hatred towards the opposing groups are evidenced to buffer negative behavioral impacts, revealing an effective psychological mechanism among fans. These findings shed light on the dual psycho-behavioral impacts of online abuse on sports fans and provide practical implications for addressing online incivility and mitigating its toxic effects on sports communication and management.

Sports, traditionally pregnant with aggression and violence, are now a breeding ground for online abuse, where toxicity and malicious campaigns on social media have even afflicted national sports role models together with their huge fan base. Drawing on an online survey of 917 Chinese volleyball enthusiasts, this study investigated the psycho-behavioral outcomes of sports fans' social media exposure to abusive messages about their idols through the lens of rejection-(dis)identification theory. Findings indicate that fans' subjective frequency of negative social media exposure is significantly negatively associated with their sport-related well-being but has no direct connection with their offline sport engagement. The study particularly delves into the mediating roles of fans' multiple identities, namely sport identity as a competitive mediator and national identity as a complementary mediator. Furthermore, with multi-group structural equation modeling and mediation analyses on gender sub-groups, gender differences were determined such that male fans, compared with female fans, were more likely to marshal their identity capital, which effectively enhanced their well-being and participation in sports. By linking classic theoretical propositions, this study offers a nuanced understanding of the sociopsychological consequences of online abuse in sports for ordinary social media users, contributing to both theoretical insights and practical implications.

Vision and aesthetics are inseparable dimensions of national image building. Based on 106,562 China-related images from Twitter (renamed as X), this paper introduced a computational aesthetic approach to investigate the visual communication activities of social bots on Twitter and compared the similarities and differences between human and bot accounts’ posted images so as to explore the influence of social bots’ aesthetic strategies. The results show that social bots have displayed different aesthetic strategies in the construction of the China-related visual frame, and formed obvious stylistic differences with humans in brightness, saturation, color, etc. Negative binomial regression indicates that the aesthetic strategies of social bots contribute to more likes and shares. The automation of visual communication and aesthetic construction not only makes the global building and communication of national image face new situations and challenges, but also pushes the whole human visual aesthetic, creation, and communication activities under the potential subjectivity crisis.

视觉与美学是国家形象研究绕不开的维度.以Twitter涉中议题下106562张图片为研究对象,通过引入计算美学方法,对社交机器人在涉中议题上的视觉传播活动进行考察,并比较人、机用户在视觉表达上的异同,探析机器用户的美学策略对传播效果的影响.结果表明,机器用户在涉中图像上已展现出有别于人类用户的美学策略,在亮度、饱和度、色彩使用等特征上形成了差异化的美学风格,这种美学风格被证明有正向的传播效果,更易获得社媒用户的点赞并触发再传播.美学策略的自动化令国家形象的对外建设、全球传播面临新态势,甚至可能将人类的视觉审美、创作与传播活动推置于主体性危机之中.

In the algorithmic society, personal privacy is exposed to ever-growing risks since the platform requires huge volumes of data for algorithm training. Globally, ordinary users, faced with the formidable platform and black-boxed algorithm, usually feel powerless against elusive privacy invasion and then have set about turning to third-party proxy institutions like the government and legislature to counterbalance the algorithmic privacy security framework. Starting from it, the present study examines what triggers users' support for third-party proxy control, and a moderated serial mediation model has been estimated based on a Chinese cross-sectional sample (N = 661). Our research suggests that users' algorithm awareness and their presumed algorithmic privacy risk to self and others (elders and minors) significantly predict their support, and serial mediating effects of the presumed algorithmic privacy risk can be more pronounced at the higher level of perceived effectiveness of platform policy. These findings help to identify the crucial role of algorithm awareness, which equips users to navigate risk and behave as responsible digital citizens, and also extend the influence of presumed influence model and the control agency theory in algorithmic contexts, making contributions in both theory and practice.

智能技术正深度嵌入社会生活.本文从技术、平台、社会三个层面展开,采用舆情小样本分析法分析2022年微博智能技术十大舆情热点.结果表明,元宇宙、数字人、Al绘画、ChatGPT等技术热点中贯穿着舆论对于技术的感知想象;IP属地开放、算法新规落地与适老化改造等公共话题体现了政策对智能技术应用的导向作用;数字灵堂、数据泄露与网课爆破等议题,表达了舆论对人本价值的要求和人文关怀.此外,多个案例样本表明,娱乐化是推动智能技术在公共范围内大规模传播的重要策略.