Investigating Perceived Message Credibility and Detection Accuracy of Fake and Real Information Across Information Types and Modalities.

Yu Chia Tseng; Chien Wen Tina Yuan

doi:10.1145/3544549.3585719

Investigating Perceived Message Credibility and Detection Accuracy of Fake and Real Information Across Information Types and Modalities.

Yu Chia Tseng, Chien Wen Tina Yuan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

(Mis-)information thrives on social media, so it has become increasingly important for users to tell real from misleading content because erroneously following misinformation can cause serious consequences. In this study, we investigated users' subjective perceived information credibility and objective detection accuracy of fake and real information across three topics, each of which was delivered via two modalities. We conducted an online within-subject experiment (n = 293) with a three (information topics: health, science, and life) by two (modalities: text and image) by two (veracity: real and fake) design. Overall, our participants were better at identifying fake information from real information. Results also found that information types significantly mediated information modality and veracity. For real information, the text mode helped people perceive credibility in health, life, and science topics. However, for false information, the image mode helped raised the perceived credibility of life information than the text mode.

Original language	English
Title of host publication	CHI 2023 - Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems
Publisher	Association for Computing Machinery
ISBN (Electronic)	9781450394222
DOIs	https://doi.org/10.1145/3544549.3585719
Publication status	Published - 2023 Apr 19
Externally published	Yes
Event	2023 CHI Conference on Human Factors in Computing Systems, CHI 2023 - Hamburg, Germany Duration: 2023 Apr 23 → 2023 Apr 28

Publication series

Name	Conference on Human Factors in Computing Systems - Proceedings

Conference

Conference	2023 CHI Conference on Human Factors in Computing Systems, CHI 2023
Country/Territory	Germany
City	Hamburg
Period	2023/04/23 → 2023/04/28

Keywords

Information modality
detection accuracy
information topics
information veracity
perceived message credibility

ASJC Scopus subject areas

Human-Computer Interaction
Computer Graphics and Computer-Aided Design
Software

Access to Document

10.1145/3544549.3585719

Cite this

Tseng, Y. C., & Yuan, C. W. T. (2023). Investigating Perceived Message Credibility and Detection Accuracy of Fake and Real Information Across Information Types and Modalities. In CHI 2023 - Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems Article 187 (Conference on Human Factors in Computing Systems - Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3544549.3585719

Investigating Perceived Message Credibility and Detection Accuracy of Fake and Real Information Across Information Types and Modalities. / Tseng, Yu Chia; Yuan, Chien Wen Tina.
CHI 2023 - Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2023. 187 (Conference on Human Factors in Computing Systems - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tseng, YC & Yuan, CWT 2023, Investigating Perceived Message Credibility and Detection Accuracy of Fake and Real Information Across Information Types and Modalities. in CHI 2023 - Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems., 187, Conference on Human Factors in Computing Systems - Proceedings, Association for Computing Machinery, 2023 CHI Conference on Human Factors in Computing Systems, CHI 2023, Hamburg, Germany, 2023/04/23. https://doi.org/10.1145/3544549.3585719

Tseng YC, Yuan CWT. Investigating Perceived Message Credibility and Detection Accuracy of Fake and Real Information Across Information Types and Modalities. In CHI 2023 - Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. 2023. 187. (Conference on Human Factors in Computing Systems - Proceedings). doi: 10.1145/3544549.3585719

Tseng, Yu Chia ; Yuan, Chien Wen Tina. / Investigating Perceived Message Credibility and Detection Accuracy of Fake and Real Information Across Information Types and Modalities. CHI 2023 - Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2023. (Conference on Human Factors in Computing Systems - Proceedings).

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title = "Investigating Perceived Message Credibility and Detection Accuracy of Fake and Real Information Across Information Types and Modalities.",

abstract = "(Mis-)information thrives on social media, so it has become increasingly important for users to tell real from misleading content because erroneously following misinformation can cause serious consequences. In this study, we investigated users' subjective perceived information credibility and objective detection accuracy of fake and real information across three topics, each of which was delivered via two modalities. We conducted an online within-subject experiment (n = 293) with a three (information topics: health, science, and life) by two (modalities: text and image) by two (veracity: real and fake) design. Overall, our participants were better at identifying fake information from real information. Results also found that information types significantly mediated information modality and veracity. For real information, the text mode helped people perceive credibility in health, life, and science topics. However, for false information, the image mode helped raised the perceived credibility of life information than the text mode.",

keywords = "Information modality, detection accuracy, information topics, information veracity, perceived message credibility",

author = "Tseng, {Yu Chia} and Yuan, {Chien Wen Tina}",

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AB - (Mis-)information thrives on social media, so it has become increasingly important for users to tell real from misleading content because erroneously following misinformation can cause serious consequences. In this study, we investigated users' subjective perceived information credibility and objective detection accuracy of fake and real information across three topics, each of which was delivered via two modalities. We conducted an online within-subject experiment (n = 293) with a three (information topics: health, science, and life) by two (modalities: text and image) by two (veracity: real and fake) design. Overall, our participants were better at identifying fake information from real information. Results also found that information types significantly mediated information modality and veracity. For real information, the text mode helped people perceive credibility in health, life, and science topics. However, for false information, the image mode helped raised the perceived credibility of life information than the text mode.

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Investigating Perceived Message Credibility and Detection Accuracy of Fake and Real Information Across Information Types and Modalities.

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