Accost, Accede, or Amplify: Attitudes towards COVID-19 Misinformation on WhatsApp in India

Varanasi, Rama Adithya; Pal, Joyojeet; Vashistha, Aditya

doi:10.1145/3491102.3517588

Cited by 16 publications

(7 citation statements)

References 74 publications

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“…Trust can be defined as "a psychological state comprising the intention to accept vulnerability based upon positive expectations of the intentions or behavior of another" [145]. Trust is, therefore, a psychological construct, and it was one of the central drivers of opinion formation [79,80] and belief change for the works reviewed in this dimension [52]. Trust in celebrities, namely, parasocial relationships [65], and social network INFLs was exploration topics.…”

Section: Resultsmentioning

confidence: 99%

“…Trust in celebrities, namely, parasocial relationships [65], and social network INFLs was exploration topics. It was seen that INFLs can significantly affect people's opinions on different issues [52,54] and that trust in the information source is an essential driver of belief change. Trust in government and officials was correlated with the consistency of the public messaging, affecting online belief change [70].…”

Section: Resultsmentioning

confidence: 99%

“…The connectivity between the traumatic public events and the arousal of emotional processes was demonstrated. Examples are the historical and institutional racism added to historical TRMAs such as the Tuskegee syphilis study [153] and the unethical and nonconsensual use of cancer cells from Henrietta Lacks [154] providing context for understanding vaccine hesitancy among Black individuals and their distrust of healthcare professionals and researchers [52]. A CRIS also evokes emotional responses that lead to polarization.…”

Section: Domain-specific Dimension As Shown In Tablementioning

confidence: 99%

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Online Fake News Opinion Spread and Belief Change: A Systematic Review

Altoe,

Moreira,

Pinto

et al. 2024

Human Behavior and Emerging Technologies

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Fake news has been linked to the rise of psychological disorders, the increased disbelief in science, and the erosion of democracy and freedom of speech. Online social networks are arguably the main vehicle of fake news spread. Educating online users with explanations is one way of preventing this spread. Understanding how online belief is formed and changed may offer a roadmap for such education. The literature includes surveys addressing online opinion formation and polarization; however, they usually address a single domain, such as politics, online marketing, health, and education, and do not make online belief change their primary focus. Unlike other studies, this work is the first to present a cross-domain systematic literature review of user studies, methodologies, and opinion model dimensions. It also includes the orthogonal polarization dimension, focusing on online belief change. We include peer-reviewed works published in 2020 and later found in four relevant scientific databases, excluding theoretical publications that did not offer validation through dataset experimentation or simulation. Bibliometric networks were constructed for better visualization, leading to the organization of the papers that passed the review criteria into a comprehensive taxonomy. Our findings show that a person’s individuality is the most significant influential force in online belief change. We show that online arguments that balance facts with emotionally evoking content are more efficient in changing their beliefs. Polarization was shown to be cross-correlated among multiple subjects, with politics being the central polarization pole. Polarized online networks start as networks with high opinion segregation, evolve into subnetworks of consensus, and achieve polarization around social network influencers. Trust in the information source was demonstrated to be the chief psychological construct that drives online users to polarization. This shows that changing the beliefs of influencers may create a positive snowball effect in changing the beliefs of polarized online social network users. These findings lay the groundwork for further research on using personalized explanations to reduce the harmful effects of online fake news on social networks.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Domain-specific Dimension As Shown In Tablementioning

confidence: 99%

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Online Fake News Opinion Spread and Belief Change: A Systematic Review

Altoe,

Moreira,

Pinto

et al. 2024

Human Behavior and Emerging Technologies

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“…A limitation of the empowerment brought about by our tool is the inherent limitation of browser extensions-that they only work on desktop and not on mobile browsers or within mobile applications. This is unfortunate especially because certain messaging apps such as WhatsApp have been a hotbed of misinformation [97]. To partially address this issue, we can provide databases or platforms such as [51] where users can copy and paste in-app messages or links to assess them or see their assessments.…”

Section: Limitationsmentioning

confidence: 99%

A Browser Extension for in-place Signaling and Assessment of Misinformation

Jahanbakhsh,

Karger

2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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“…Misinformation is now a common digital threat of the modern era and its resultant damage should be a cause for concern for HCI researchers, as it is interactions with digital tools that can expose users to misinforming content. HCI research has identifed areas of misinformation spread from a corporate perspective [29], difculties addressing misinformation in the media [41], and the impact of social status on infuencing engagement with misinformation [62]. Empirical research into misinformation interventions typically falls into one of two main categories: prevention, or cure.…”

Section: Misinformation Interventionsmentioning

confidence: 99%

“I figured her feeling a little bit bad was worth it to not spread that kind of hate”: Exploring how UK families discuss and challenge misinformation

Scott

Coventry

Cecchinato

et al. 2023

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

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Misinformation has become a regular occurrence in our lives with many diferent approaches being sought to address it. One efective way to combat misinformation is for trusted individuals (e.g., family members) to challenge the misinformed person. However, less is known about how these conversations between trusted individuals occur, and how they may impact on relationships. We look to address this gap by conducting semi-structured interviews with family members in the UK who have experienced misinformation within their family networks. We identify several barriers individuals face when challenging misinformed family members, such as the misinformed person's personality and the extent that preconceptions infuence beliefs. We also fnd individuals developing strategies to overcome these barriers, and to cope with difculties that arise through these conversations. Despite technology being the main driver for misinformation spread, we fnd it has limitations when used to facilitate or mediate conversations for challenging misinformation between family members. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI.

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Accost, Accede, or Amplify: Attitudes towards COVID-19 Misinformation on WhatsApp in India

Cited by 16 publications

References 74 publications

Online Fake News Opinion Spread and Belief Change: A Systematic Review

Online Fake News Opinion Spread and Belief Change: A Systematic Review

A Browser Extension for in-place Signaling and Assessment of Misinformation

“I figured her feeling a little bit bad was worth it to not spread that kind of hate”: Exploring how UK families discuss and challenge misinformation

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