Dissemination of Fact-Checked News Does Not Combat False News: Empirical Analysis

Jing, Z; Suleiman, B; Yaqub, W; Mohanty, M

Dissemination of Fact-Checked News Does Not Combat False News: Empirical Analysis

Jing, Z Suleiman, B Yaqub, W Mohanty, M

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Publisher:: Springer Nature
Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2023, 14306 LNCS, pp. 122-133
Issue Date:: 2023-01-01

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Field	Value	Language
dc.contributor.author	Jing, Z
dc.contributor.author	Suleiman, B
dc.contributor.author	Yaqub, W
dc.contributor.author	Mohanty, M https://orcid.org/0000-0002-0258-4586
dc.date.accessioned	2024-06-05T01:13:29Z
dc.date.available	2024-06-05T01:13:29Z
dc.date.issued	2023-01-01
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2023, 14306 LNCS, pp. 122-133
dc.identifier.isbn	9789819972531
dc.identifier.issn	0302-9743
dc.identifier.issn	1611-3349
dc.identifier.uri	http://hdl.handle.net/10453/179396
dc.description.abstract	This paper examines the impact of true news on the propagation of false news in social media networks. Due to the unavailability of real-world data, we present our methodological approach for collecting Twitter data using the Twitter API. Our dataset includes about five million tweets over six months, encompassing 400 false news stories with fact-checker labels, verified true news tweets, and related interactions (retweets, quoted tweets, replies). Our analysis investigates the influence of true news on curbing false news dissemination on Twitter and explores potential user network connections between false and true news. Statistical analysis on the dataset suggests that true news tweets have an insignificant impact on the spread of false news tweets. These results contribute to our understanding of the dynamics between true and false news within social media networks.
dc.language	en
dc.publisher	Springer Nature
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.ispartofseries	Lecture Notes in Computer Science
dc.relation.isbasedon	10.1007/978-981-99-7254-8_10
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Artificial Intelligence & Image Processing
dc.subject.classification	46 Information and computing sciences
dc.title	Dissemination of Fact-Checked News Does Not Combat False News: Empirical Analysis
dc.type	Conference Proceeding
utslib.citation.volume	14306 LNCS
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Science
pubs.organisational-group	University of Technology Sydney/Strength - CFS - Centre for Forensic Science
pubs.organisational-group	University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access	*
dc.date.updated	2024-06-05T01:13:26Z
pubs.publication-status	Published
pubs.volume	14306 LNCS

Abstract:

This paper examines the impact of true news on the propagation of false news in social media networks. Due to the unavailability of real-world data, we present our methodological approach for collecting Twitter data using the Twitter API. Our dataset includes about five million tweets over six months, encompassing 400 false news stories with fact-checker labels, verified true news tweets, and related interactions (retweets, quoted tweets, replies). Our analysis investigates the influence of true news on curbing false news dissemination on Twitter and explores potential user network connections between false and true news. Statistical analysis on the dataset suggests that true news tweets have an insignificant impact on the spread of false news tweets. These results contribute to our understanding of the dynamics between true and false news within social media networks.

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http://hdl.handle.net/10453/179396