Cyberbullying has become a critical social issue, which severely threatens children and adolescents’ physical and psychological health. The current research systematically examined the predictors of cyberbullying from the social cognitive and media effects approach. Specifically, this study identified 16 predictors of cyberbullying perpetration and victimization and examined the magnitude of the effects of these predictors by meta-analyzing 81 empirical studies, which represented a total sample of 99,741 participants and yielded 259 independent correlations. The results revealed that risky information and communications technology (ICT) use, moral disengagement, depression, social norms, and traditional bullying perpetration were the main predictors of cyberbullying perpetration, while risky ICT use and traditional bullying victimization were the major contributors of cyberbullying victimization. According to the moderator analyses, country of the sample, sampling method, age, and media platform were significant moderators of the relationships between some specific predictors and cyberbullying perpetration and victimization. Implications for future cyberbullying research were discussed.

Background: Over the last two decades, the incidence and mortality rates of gynecologic cancers have increased at a constant rate in China. Gynecologic cancers have become one of the most serious threats to women’s health in China. With the widespread use of social media, an increasing number of individuals have employed social media to produce, seek, and share cancer-related information. However, health information on social media is not always accurate. Health, and especially cancer-related, misinformation has been widely spread on social media, which can affect individuals’ attitudinal and behavioral responses to cancer.Objective: The aim of this study was to examine the nature and diffusion of gynecologic cancer–related misinformation on Weibo, the Chinese equivalent of Twitter.Methods: A total of 2691 tweets related to 2 gynecologic cancers—breast cancer and cervical cancer—posted on Weibo from June 2015 to June 2016 were extracted using the Python Web Crawler. Two medical school graduate students with expertise in gynecologic diseases were recruited to code the tweets to differentiate between true information and misinformation as well as to identify the types of falsehoods. The diffusion characteristics of gynecologic cancer–related misinformation were compared with those of the true information.Results: While most of the gynecologic cancer–related tweets provided medically accurate information, approximately 30% of them were found to contain misinformation. Furthermore, it was found that tweets about cancer treatment contained a higher percentage of misinformation than prevention-related tweets. Nevertheless, the prevention-related misinformation diffused significantly more broadly and deeply than true information on social media.Conclusions: The findings of this study suggest the need for controlling and reducing the cancer-related misinformation on social media with the efforts from both service providers and medical professionals. More specifically, it is important to correct falsehoods related to the prevention of gynecologic cancers on social media and increase individuals’ capacity to assess the veracity of Web-based information to curb the spread and thus minimize the consequences of cancer-related misinformation.

Purpose: Drawing on the third-person effect (TPE) theory and the theory of planned behavior (TPB) as a theoretical framework, the current study aims to explore the cognitive mechanisms behind how third-person perception (TPP) of misinformation about public health emergencies affects intention to engage in corrective actions via attitude, subjective norms and perceived behavioral control.Design/methodology/approach: A total of 1,063 participants in China were recruited via a professional survey company (Sojump) to complete an online national survey during the outbreak of coronavirus (COVID-19) in China. Structural equation modeling using Mplus 7.0 was used to address the research hypotheses.Findings: The results reveal that attention to online information about public health emergencies significantly predicted TPP. In addition, TPP positively influenced attitude and perceived behavioral control, which, in turn, positively encouraged individuals to take corrective actions to debunk online misinformation. However, TPP did not significantly influence subjective norms. A potential explanation is provided in the discussion section.Research limitations/implications: The research extends the TPE theory by providing empirical evidence for corrective actions and uncovers the underlying cognitive mechanism behind the TPE by exploring key variables of the TPB as mediating constructs. These are all significant theoretical contributions to the TPE and offer practical contributions to combating online misinformation.Originality/value: The research extends the TPE theory by providing empirical evidence for a novel behavioral outcome (i.e. corrective actions in response to misinformation) and uncovers the cognitive mechanism underlying the TPE by exploring key variables of the TPB as mediating constructs. These are all significant theoretical contributions to the TPE and offer practical contributions to combating online misinformation.

Following the COVID-19’s outbreak in China, wildlife-related issues such as wildlife management and conservation made headlines around the world due to the potential zoonotic nature of the newly discovered coronavirus. In our study, we examined the dynamic interaction of the news agenda and public agenda concerning wildlife-related issues on social media after COVID-19’s outbreak. Using big data analytics, we automatically extracted the agendas’ attributes and networks from 110,549 social media posts made from January 1 to April 8, 2020, and investigated the effect of second- and third-level dynamic agenda setting in a time series analysis. Our findings suggest that the agenda-setting effect of wildlife-related issues on social media was not a single-step, unidirectional action but a reciprocal, dynamic interaction constantly constructed by news outlets and the general public.

Background: Cancer ranks among the most serious public health challenges worldwide. In China—the world’s most populous country—about one-quarter of the population consists of people with cancer. Social media has become an important platform that the Chinese public uses to express opinions. Objective: We investigated cancer-related discussions on the Chinese social media platform Weibo (Sina Corporation) to identify cancer topics that generate the highest levels of user engagement. Methods: We conducted topic modeling and regression analyses to analyze and visualize cancer-related messages on Weibo and to examine the relationships between different cancer topics and user engagement (ie, the number of retweets, comments, and likes). Results: Our results revealed that cancer communication on Weibo has generally focused on the following six topics: social support, cancer treatment, cancer prevention, women’s cancers, smoking and skin cancer, and other topics. Discussions about social support and cancer treatment attracted the highest number of users and received the greatest numbers of retweets, comments, and likes. Conclusions: Our investigation of cancer-related communication on Weibo provides valuable insights into public concerns about cancer and can help guide the development of health campaigns in social media.