Reflective and Formative Indicators of Information Credibility on Social Media

ABSTRACT As part of a larger project to develop a scale for measuring web credibility perceptions, this poster reports on preliminary findings of a literature analysis to identify reflective and formative indicators of information credibility on social media. Of 90 papers found by a systematic database search and screening, this poster examines 20 papers focused on information credibility on microblogs (e.g., Twitter, Weibo) as a popular source for online users' information seeking. Our analysis identified 22 reflective indicators (e.g., fair, accurate) and 31 formative indicators (e.g., reputable, attractive), eight (e.g., trustworthy, unbiased) of which overlapped. Given the intertwined, often blurred border between these two sets of items, the coding scheme developed in the present study can help determine the relevance and type of the items. Future research directions are discussed.

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Publication Details

Journal
Proceedings of the Association for Information Science and Technology
Published
2024-10-01
DOI
https://doi.org/10.1002/pra2.1125
Citations
1
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
1.13
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article

Reflective and Formative Indicators of Information Credibility on Social Media

Wonchan Choi, Hyun Seung Lee, Liya Zhu
1 citations
Proceedings of the Association for Information Science and Technology
Misinformation and Its Impacts
1.13
article

Reflective and Formative Indicators of Information Credibility on Social Media

Wonchan Choi, Hyun Seung Lee, Liya Zhu
article en
1 citations

Abstract

ABSTRACT As part of a larger project to develop a scale for measuring web credibility perceptions, this poster reports on preliminary findings of a literature analysis to identify reflective and formative indicators of information credibility on social media. Of 90 papers found by a systematic database search and screening, this poster examines 20 papers focused on information credibility on microblogs (e.g., Twitter, Weibo) as a popular source for online users' information seeking. Our analysis identified 22 reflective indicators (e.g., fair, accurate) and 31 formative indicators (e.g., reputable, attractive), eight (e.g., trustworthy, unbiased) of which overlapped. Given the intertwined, often blurred border between these two sets of items, the coding scheme developed in the present study can help determine the relevance and type of the items. Future research directions are discussed.

Proceedings of the Association for Information Science and TechnologyVol. 61(1)
University of Wisconsin–Milwaukee (US)
Openalex Percentile: Top 16%
Misinformation and Its Impacts
1.13
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