An Analysis of Rumor and Counter-Rumor Messages in Social Media

The “Parallel Pandemic” in the Context of China: The Spread of Rumors and Rumor-Corrections During COVID-19 in Chinese Social Media

“…Moreover, the effects of source type were noteworthy. Consistent with prior findings (e.g., Chua, Tee, et al, 2017;Goh et al, 2017), the sources that the public deemed more legitimate than ordinary users were more effective in enhancing retransmission of both rumors and rumor-corrections. The role of news aggregators was prominent in the retransmission of rumor-correction messages: The likelihood of a news aggregator's post being shared was 53 times higher than that of ordinary users, while other legitimate sources such as government authority and traditional media were only about 13 times more or so.…”

“…On social media, the community of users collectively contribute to disseminating rumors and rumor-correction messages. While research has suggested that online communities have the capacity of self-correction and self-policing, rumor-correction messages have been found at times to be ineffective and even to intensify misperceptions ( Goh et al, 2017 ). Drawing from literature on social sharing of news contents ( Berger & Milkman, 2012 ; Stieglitz & Dang-Xuan, 2013 ), we examine the impact of rumor types, frames, and source characteristics on sharing rumor and corrective messages.…”

Why people spread rumors on social media: developing and validating a multi-attribute model of online rumor dissemination

“…The current study addresses this gap by providing experimental evidence that informational characteristics of online rumors can trigger rumor forwarding behavior through the psychological mediators under the S-O-R framework (Mehrabian and Russell, 1974), which provides an overarching paradigm linking the information characteristics of online rumors (stimuli), psychological motivations (organism) and rumor dissemination (response). The results of the current study complement the extant literature of mathematical modeling (Chua and Banerjee, 2017;Goh et al, 2017;Kim and Bock, 2011;Liu et al, 2014;Oh et al, 2016) by improving our understanding of people's behavior of transmitting online rumors.…”

“…A review of the relevant literature reveals that most studies have approached the issue by analyzing the semantic networks of online rumor transmission at the group level (Chua and Banerjee, 2017;Goh et al, 2017;Kim and Bock, 2011;Liu et al, 2014;Oh et al, 2016), revealing that although numerous topics related to online rumors have been addressed, relatively little attention has been directed toward the specific informational characteristics of online rumors themselves that influence recipients' rumor-forwarding behavior. The present study attempts to fill this gap by providing a model of online rumors that relates to the informational characteristics of online rumors and recipients' motivational characteristics to explain online rumor-forwarding behavior.…”

Effective ways to combat online medical and scientific misinformation: A hermeneutic narrative review and analysis

“…Therefore, any interventions aimed at the information consumer must consider both the environment and motivations of the user. On Twitter, for example, users often try various techniques to debunk rumors, from providing evidence for refutation, expressing disbelief, employing sarcasm, or suggesting actions to refute the rumor (Goh et al, 2017). At least some types of people, like journalists, are more likely to correct misinformation on Twitter (Arif et al, 2017;Starbird et al, 2018), suggesting that some behaviors aiming to stop the amplification and influence of misinformation can be promoted.…”