Performance Analysis of Fact-Checking Organisations and Initiatives in Europe: A Critical Overview of Online Platforms Fighting Fake News

Pavleska, Tanja; Školkay, Andrej; Zankova, Bissera; Ribeiro, Nelson; Bechmann, Anja

doi:10.1017/9781839700422.014

Cited by 8 publications

(6 citation statements)

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“…Moreover, such a solution on the platform-side does not empower people to better recognize and cope with fake news that potentially reaches them through other channels. Alternatively, professional fact-checkers who publish objective evaluations of widely circulated claims could be effective in countering fake news (Pavleska et al, 2018). However, fact-checkers need time and funding to verify news and debunking false beliefs in people's minds is difficult (see meta-analysis Chan et al, 2017).…”

mentioning

confidence: 99%

Stop and Think! Exploring the Role of News Truth Discernment, Information Literacy, and Impulsivity in the Effect of Critical Thinking Recommendations on Trust in Fake Covid-19 News

Kruijt

Meppelink

Vandeberg³

2022

EJHC

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Covid-19-related fake news widely circulates on social media. This is problematic as people commonly do not process information on social media in a very critical manner. Also, when people encounter particular online content several times this tends to increase the content’s trustworthiness, sometimes irrespective of the accuracy of the provided information. Our study aims to explore whether, how, and for whom a simple critical thinking recommendation added to a social media newsfeed can aid people to better discern true news from fake news and reduce their trust in fake news. In an online experiment, 220 participants were exposed to a Twitter newsfeed with true and fake Covid-19-related news messages, either with or without critical thinking recommendations. The findings showed that participants who were exposed to the recommendations showed less trust in fake news messages, which was mediated by an increased accuracy in news truth discernment. Results showed no significant moderating effects of information literacy and impulsivity characteristics. Overall, the findings of this study are promising as this scalable, low-cost intervention might potentially help combat the effects of fake news on social media.

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confidence: 99%

Stop and Think! Exploring the Role of News Truth Discernment, Information Literacy, and Impulsivity in the Effect of Critical Thinking Recommendations on Trust in Fake Covid-19 News

Kruijt

Meppelink

Vandeberg³

2022

EJHC

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“…Bots programmed as users on social networks acted to generate content and interact with humans, or other bot users, increasing misleading news (Ferrara, et al, 2016;Chu, et al, 2012). These technologies have also been used to eradicate fake news (Della Vedova, et al, 2018), as practised by fact-checking organisations (Ceron, et al, 2021;Pavleska, et al, 2018). Facebook and Google have also launched fact-checking projects.…”

Section: Background Literaturementioning

confidence: 99%

'No, auntie, that's false': Challenges and resources of female baby boomers dealing with fake news on Facebook

Vargas-Bianchi

Mateus

Pecho-Ninapaytan

et al. 2023

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The spread of fake news on social media networks is on the rise, prompting a special interest in identification and coping skills among news consumers so that they can filter out misleading information. Studies suggest seniors share more fake news on social media; despite this, there is little literature analysing how they behave when faced with fake news. This study examines how baby boomer women handle fake news on Facebook, and the role of family members in contributing to their digital literacy in dealing with this phenomenon. A qualitative thematic analysis study was conducted using information obtained from interviews; the findings revealed that participants recognised that they could identify fake news, but were not always able to do so because of a lack of supplemental information about the news’ context or doubt about its source. Interviewees also revealed that they turned to trusted family members to assist them in developing fake news identification and filtering skills.

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“…Crowd-generated counter-misinformation complements fact-checking and correction by professionals -the latter has already been studied extensively [32,33,67,77,110,117]. Emerging research has analyzed the role that non-experts play in flagging and countering misinformation.…”

Section: Analysis Of Crowd-generated Misinformation Flagging and Coun...mentioning

confidence: 99%

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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Performance Analysis of Fact-Checking Organisations and Initiatives in Europe: A Critical Overview of Online Platforms Fighting Fake News

Cited by 8 publications

References 0 publications

Stop and Think! Exploring the Role of News Truth Discernment, Information Literacy, and Impulsivity in the Effect of Critical Thinking Recommendations on Trust in Fake Covid-19 News

Stop and Think! Exploring the Role of News Truth Discernment, Information Literacy, and Impulsivity in the Effect of Critical Thinking Recommendations on Trust in Fake Covid-19 News

'No, auntie, that's false': Challenges and resources of female baby boomers dealing with fake news on Facebook

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

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