Message content in the life of rumors: Comparing three rumor types

Chua, Alton Y. K.; Aricat, Rajiv George; Goh, Dion Hoe‐Lian

doi:10.1109/icdim.2017.8244643

Cited by 12 publications

(8 citation statements)

References 26 publications

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“…In research addressing users' online comments, scholars have focused on information-seeking and information-sharing behaviors and even the nature of affective factors such as emotions and feelings. For instance, categorizing users' comments on Twitter posts with rumors as emotion-related, information-related, deliberative or calling for action, Chua et al (2017) found that most discussions were emotion- or information-related ones. Along similar lines, Zhang et al (2013) have suggested that users' interactions in a Facebook diabetes group were structured around information, emotion and community-building.…”

Section: Interaction Between Communities: Like-minded and Cross-cutting Discussionmentioning

confidence: 99%

Viral misinformation and echo chambers: the diffusion of rumors about genetically modified organisms on social media

Wang

Song

2020

INTR

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PurposeThe spread of rumors on social media has caused increasing concerns about an under-informed or even misinformed public when it comes to scientific issues. However, researchers have rarely investigated their diffusion in non-western contexts. This study aims to systematically examine the content and network structure of rumor-related discussions around genetically modified organisms (GMOs) on Chinese social media.Design/methodology/approachThis study identified 21,837 rumor-related posts of GMOs on Weibo, one of China's most popular social media platforms. An approach combining social network analysis and content analysis was employed to classify user attitudes toward rumors, measure the level of homophily of their attitudes and examine the nature of their interactions.FindingsThough a certain level of homophily existed in the interaction networks, referring to the observed echo chamber effect, Weibo also served as a public forum for GMO discussions in which cross-cutting ties between communities existed. A considerable amount of interactions emerged between the pro- and anti-GMO camps, and most of them involved providing or requesting information, which could mitigate the likelihood of opinion polarization. Moreover, this study revealed the declining role of traditional opinion leaders and pointed toward the need for alternative strategies for efficient fact-checking.Originality/valueIn general, the findings of this study suggested that microblogging platforms such as Weibo can function as public forums for discussing GMOs that expose users to ideologically cross-cutting viewpoints. This study stands to provide important insights into the viral processes of scientific rumors on social media.

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Section: Interaction Between Communities: Like-minded and Cross-cutting Discussionmentioning

confidence: 99%

Viral misinformation and echo chambers: the diffusion of rumors about genetically modified organisms on social media

Wang

Song

2020

INTR

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“…Rosnow et al (1986) identify three types of rumors: wish, dread, and wedge-driving. We define wish rumors as rumors that project hope by positing positive outcomes; dread rumors as fear-invoking rumors that hint at negative outcomes; wedge-driving rumors promulgate hatred and division by instigating anger and hostility among audiences (Chua, Aricat, & Goh, 2017). Rumor type was coded as 0 = wish , 1 = dread , and 2 = wedge-driving , with wish as the reference group (Krippendorff’s α = .93).…”

Section: Methodsmentioning

confidence: 99%

“…Knapp (1944) introduced a taxonomy of three types of rumor: (1) "pipe-dream" rumors: rumors that lead to wishful thinking, (2) "bogy" rumors: dread rumors that increase anxiety or fear, and (3) "wedge-driving" rumors: those that generate hatred. In a recent study of Twitter, Chua, Aricat, and Goh (2017) discovered that wish, dread, and wedge-driving are distinguished not only by their underlying emotional appeal but also by their content categories, such as whether the rumor is information-related or of deliberation. Nonetheless, which type of rumor is more likely to go viral and how rumor type affects the sharing of rumors and rumor-corrections in situations have received limited attention.…”

Section: Characterizing Rumors and Correction Messagesmentioning

confidence: 99%

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

Song

Kwon

Yin

et al. 2021

American Behavioral Scientist

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Although studies have investigated cyber-rumoring previous to the pandemic, little research has been undertaken to study rumors and rumor-corrections during the COVID-19 (coronavirus disease 2019) pandemic. Drawing on prior studies about how online stories become viral, this study will fill that gap by investigating the retransmission of COVID-19 rumors and corrective messages on Sina Weibo, the largest and most popular microblogging site in China. This study examines the impact of rumor types, content attributes (including frames, emotion, and rationality), and source characteristics (including follower size and source identity) to show how they affect the likelihood of a COVID-19 rumor and its correction being shared. By exploring the retransmission of rumors and their corrections in Chinese social media, this study will not only advance scholarly understanding but also reveal how corrective messages can be crafted to debunk cyber-rumors in particular cultural contexts.

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“…This message created panic among the citizens, as the misinformation was shared more than 7000 times on Facebook [61]. Wish is the type of rumor that gives hope to the receiver (e.g.,: rumor on free medicine distribution) [62]. Dread rumor looks more trustworthy and more likely to get viral.…”

Section: Characterizing Healthcare Misinformationmentioning

confidence: 99%

The disaster of misinformation: a review of research in social media

Mathew

2022

Int J Data Sci Anal

128

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The spread of misinformation in social media has become a severe threat to public interests. For example, several incidents of public health concerns arose out of social media misinformation during the COVID-19 pandemic. Against the backdrop of the emerging IS research focus on social media and the impact of misinformation during recent events such as the COVID-19, Australian Bushfire, and the USA elections, we identified disaster, health, and politics as specific domains for a research review on social media misinformation. Following a systematic review process, we chose 28 articles, relevant to the three themes, for synthesis. We discuss the characteristics of misinformation in the three domains, the methodologies that have been used by researchers, and the theories used to study misinformation. We adapt an Antecedents-Misinformation-Outcomes (AMIO) framework for integrating key concepts from prior studies. Based on the AMIO framework, we further discuss the inter-relationships of concepts and the strategies to control the spread of misinformation on social media. Ours is one of the early reviews focusing on social media misinformation research, particularly on three socially sensitive domains; disaster, health, and politics. This review contributes to the emerging body of knowledge in Data Science and social media and informs strategies to combat social media misinformation.

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Message content in the life of rumors: Comparing three rumor types

Cited by 12 publications

References 26 publications

Viral misinformation and echo chambers: the diffusion of rumors about genetically modified organisms on social media

Viral misinformation and echo chambers: the diffusion of rumors about genetically modified organisms on social media

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

The disaster of misinformation: a review of research in social media

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