DOMAIN: Explainable credibility assessment tools for empowering online readers coping with misinformation DOI Open Access

Danielle Caled,

Paula Carvalho, Francisco Sousa

et al.

ACM Transactions on the Web, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 26, 2024

Despite all the fact-checking initiatives on news and social media aimed at countering misinformation, they remain insufficient to promptly address wide array of misleading information disseminated by both outlets. Rather than attempting identify or filter information, this work advocates new tools for assisting online readers in identifying misinformation among massive content pushed every day through multiple platforms. We introduce DOMAIN, an article assessment resource bundle comprising a multidimensional indicator categorize articles into different types (hard news, soft opinion, satire, conspiracy), set explanatory metrics help users understand results, tool verifying reliability article’s source, text summary assessment. This also studies how DOMAIN impact readers, specifically focusing i) understanding extent which computer-generated assessments influence human perceptions credibility; ii) evaluating effectiveness automatic categorization iii) most relevant promoting informed critical consumption information.

Language: Английский

DOMAIN: Explainable credibility assessment tools for empowering online readers coping with misinformation DOI Open Access

Danielle Caled,

Paula Carvalho, Francisco Sousa

et al.

ACM Transactions on the Web, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 26, 2024

Despite all the fact-checking initiatives on news and social media aimed at countering misinformation, they remain insufficient to promptly address wide array of misleading information disseminated by both outlets. Rather than attempting identify or filter information, this work advocates new tools for assisting online readers in identifying misinformation among massive content pushed every day through multiple platforms. We introduce DOMAIN, an article assessment resource bundle comprising a multidimensional indicator categorize articles into different types (hard news, soft opinion, satire, conspiracy), set explanatory metrics help users understand results, tool verifying reliability article’s source, text summary assessment. This also studies how DOMAIN impact readers, specifically focusing i) understanding extent which computer-generated assessments influence human perceptions credibility; ii) evaluating effectiveness automatic categorization iii) most relevant promoting informed critical consumption information.

Language: Английский

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