Journal of Risk Research

Mobile social media subscribers' unfollowing rate has remained high during natural disasters in recent years, which poses a challenge to the crisis communication during natural disasters. This manuscript uses the stressor-strain-outcome framework and media dependency theory to examine the prerequisites of mobile social media subscribers' unfollowing intention during natural disasters. It considers the negative information-related features of mobile social media. The analysis employs data gathered from 761 mobile social media subscribers in China and reveals that dissatisfaction, fatigue, and social media dependency positively affect mobile social media subscribers' unfollowing intention during natural disasters. The results reported in this manuscript enrich the existing literature on crisis communication and offer practical recommendations to mobile social media managers to avoid mass subscribers losses while sustaining existing subscriber base during natural disasters.

Risk perception plays a crucial role in risk management and risk reduction as it involves the understanding of risk exposures that can affect the stability of both financial and non-financial institutions. This research aims to elucidate the influence of risk perception on risk management during significant events. Employing a systematic literature review (SLR) methodology, this study adheres to the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) guidelines to ensure the production of high-quality evidence. The review identified 2333 unique articles, 16 meeting the inclusion criteria from online databases such as Web of Sciences, Scopus, ScienceDirect, Sage, and Wiley, spanning publications from 2007 to 2022. The majority of the reviewed articles indicate a positive correlation between risk perception and risk management. Specifically, indicated that a high level of risk perception is associated with higher adherence to risk management strategies. However, the relationship between risk perception and risk management under political conflict remains under-explored, highlighting the need for further investigation into the varying types of risk associated with political instability

Over the past decade, many experts from academia, business, and civil society have warned of the risks of artificial intelligence (AI), such as large-scale job displacement, data bias against social groups, the use of AI to undermine democracy, the misuse of AI for mass surveillance and/ or policing, the unregulated use of autonomous weapons, and others. However, research suggests that news media and social media representations emphasize the benefits over the risks of AI and rarely address issues of risk governance, while social media studies are still rare and largely based on Twitter/X data. This study proposes a theoretical framework of mediated risk communication based on the social amplification of risk framework (SARF), the extended parallel process model (EPPM), and framing. To understand prevalent AI-related risk frames and their role in mediated technological risk amplification/attenuation before and after the release of ChatGPT, a sample of the 501 most viewed YouTube videos about AI published between 2020 and 2023 were analyzed. Four frames with different emphases on societal threat and societal efficacy of AI were found with significant differences between risk/benefit emphases , AI evaluations, risk control/governance measures, and references to risk governance actors. Frames with higher emphasis on societal threat of AI were more likely to be viewed and commented on by YouTube users. AI-related threat frames increased significantly after the release of ChatGPT in 2022, suggesting its role as a risk-amplifying event. Implications for theory, future research, and AI risk governance are discussed.