The Role of Influence of Presumed Influence and Anticipated Guilt in Evoking Social Correction of COVID-19 Misinformation

Sun, Yanqing; Oktavianus, Jeffry; Wang, Sai; Lu, Fangfang

doi:10.1080/10410236.2021.1888452

Cited by 28 publications

(24 citation statements)

References 33 publications

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“…In terms of theoretical implications, first, the present study responds to urgent calls to enrich the literature on misinformation debunking. While some scholars have indicated that presumed media influence could affect misinformation correction (Sun et al, 2021), few studies have examined how TPP affects corrective actions of misinformation. Thus, it is imperative to conduct research to examine the TPE in the context of combating misinformation.…”

Section: Implications and Limitationsmentioning

confidence: 99%

Let's fight the infodemic: the third-person effect process of misinformation during public health emergencies

Chen

2022

INTR

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PurposeDrawing 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/approachA 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.FindingsThe 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/implicationsThe 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/valueThe 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.

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Section: Implications and Limitationsmentioning

confidence: 99%

Let's fight the infodemic: the third-person effect process of misinformation during public health emergencies

Chen

2022

INTR

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“…Notably, users' polite and evidenced responses that refute misinformation are shown to effectively counter misinformation and reduce the belief in misinformation [14,55,65,65,77,85,87,91]. Users correct others, typically friends [56], owing to a sense of social duty [24,30,61,66,96], anger, or guilt [88]. These works provide considerable evidence that correction by ordinary users is effective when countering misinformation and in mitigating the spread of misinformation.…”

Section: Related Work 21 Social Correction Of Misinformation By Non-e...mentioning

confidence: 97%

Reinforcement Learning-based Counter-Misinformation Response Generation: A Case Study of COVID-19 Vaccine Misinformation

Ahamad

Kumar

2023

Proceedings of the ACM Web Conference 2023

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The spread of online misinformation threatens public health, democracy, and the broader society. While professional fact-checkers form the first line of defense by fact-checking popular false claims, they do not engage directly in conversations with misinformation spreaders. On the other hand, non-expert ordinary users act as eyeson-the-ground who proactively counter misinformation -recent research has shown that 96% counter-misinformation responses are made by ordinary users. However, research also found that 2/3 times, these responses are rude and lack evidence. This work seeks to create a counter-misinformation response generation model to empower users to effectively correct misinformation. This objective is challenging due to the absence of datasets containing groundtruth of ideal counter-misinformation responses, and the lack of models that can generate responses backed by communication theories. In this work, we create two novel datasets of misinformation and counter-misinformation response pairs from in-the-wild social media and crowdsourcing from college-educated students. We annotate the collected data to distinguish poor from ideal responses that are factual, polite, and refute misinformation. We propose MisinfoCorrect, a reinforcement learning-based framework that learns to generate counter-misinformation responses for an input misinformation post. The model rewards the generator to increase the politeness, factuality, and refutation attitude while retaining text fluency and relevancy. Quantitative and qualitative evaluation shows that our model outperforms several baselines by generating high-quality counter-responses. This work illustrates the promise of generative text models for social good -here, to help create a safe and reliable information ecosystem. The code and data is accessible on https://github.com/claws-lab/MisinfoCorrect.

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“…Relatively, studies investigating population's attitude or behavior are not many (7, 13%), most of which were conducted in the USA (Cheng and Luo, 2021;Pennycook et al, 2020;Sun et al, 2021). Table 5 provides the summary.…”

Section: Attitude/behaviormentioning

confidence: 99%

“…Interestingly, feeling guilty was found to increase corrective actions among 400 respondents in the US (Sun et al, 2021), suggesting that corrective messages emphasizing susceptibility and severity regarding the effect of fake news on others can evoke emotional responses (e.g. anger or empathic) and potentially motivate others to join in combating fake news.…”

Section: Attitude/behaviormentioning

confidence: 99%

COVID-19 fake news among the general population: motives, sociodemographic, attitude/behavior and impacts – a systematic review

Balakrishnan

Rahman

Tan

et al. 2022

OIR

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PurposeThis systematic review aims to synthesize the literature reporting the motives, sociodemographic, attitude/behavior and impacts of fake news during the COVID-19 pandemic, targeting the general population worldwide.Design/methodology/approachA systematic review approach was adopted based on PRISMA, targeting articles published in five databases from January 2020 to November 2021. The screening resulted in 46 eligible papers.FindingsResults indicate low level of awareness, knowledge, media/health literacy, low trust in science/scientists and entertainment/socialization to be the main motivating drivers for fake news dissemination, whereas the phenomenon is more prominent among those with low socio-economic status, and males. Negative impacts were reported due to fake news dissemination, especially violation to precautionary measures, negative affections, and low trust in government/news, with many believing that others are more susceptible to fake news than themselves.Social implicationsConsidering the pandemic is still on-going and the deleterious consequences of fake news, there is a need for cohort-based interventions from the concerned authorities.Originality/valueThe systematic review covers a wide timeline of 23 months (i.e. up to end of 2022) targeting five well-known databases, hence articles examined are deemed extensive and comprehensive. The review specifically focused on the general population with results revealing interesting motives, sociodemographic profiles, attitude and impact of this phenomenon during the COVID-19 pandemic.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-02-2022-0082.

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The Role of Influence of Presumed Influence and Anticipated Guilt in Evoking Social Correction of COVID-19 Misinformation

Cited by 28 publications

References 33 publications

Let's fight the infodemic: the third-person effect process of misinformation during public health emergencies

Let's fight the infodemic: the third-person effect process of misinformation during public health emergencies

Reinforcement Learning-based Counter-Misinformation Response Generation: A Case Study of COVID-19 Vaccine Misinformation

COVID-19 fake news among the general population: motives, sociodemographic, attitude/behavior and impacts – a systematic review

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