Blogs of Information: How Gender Cues and Individual Motivations Influence Perceptions of Credibility
Open accessAbstract
This study examines how gender cues influence perceptions of credibility of informational blogs. Using 2 experiments for data collection, this study manipulated the gender descriptors of a Weblog authors and had participants rate the overall perceived credibility of 1 of 3 blog posts. Male authors were deemed more credible than female authors, and main effects were found for information seekers, who found the blogs more credible than noninformation seekers. Implications are discussed.
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Author gender can introduce bias because author gender impacts the experience of grief and readers' perception of authorial skills.
“This can introduce bias because (an author's) gender impacts on the experience of grief, the theme of some of our texts (Bierhals et al., 1996;Schwab, 1996), and on readers' perception of authorial skills (Armstrong & McAdams, 2009;Paludi & Strayer, 1985;Weinberg & Kapelner, 2018).”
From The effects of reading narrative fiction on social and moral cognition (2021) · cites this paper as Armstrong & McAdams, 2009
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- Cory L. Armstrong, Ph.D., is an assistant professor in the College of Journalism and Communications at the University of Florida, where she teaches information gathering, research, news writing, and diversity-related courses. Her research interests include credibility, gender portrayals and macro-level influences on news content and she has had research published in several top communication journals, including Journalism & Mass Communication Quarterly, Journal of Communication and Mass Communication & Society, where she is also an associate editor. Her recent scholarship has examined the role of gender in obesity-related news coverage. Armstrong received her master's and doctoral degrees from the University of Wisconsin-Madison and graduated with a B.A. from Miami University. She also has more than eight years of professional newspaper experience. Address: 3045
- Mindy McAdams is a professor in the Department of Journalism and Knight Chair for journalism technologies and the democratic process at the University of Florida. She teaches undergraduate courses about online journalism and a graduate course about the relationship between digital communications technologies and democracy. She is the author of Flash Journalism: How to Create Multimedia News Packages (Focal Press, 2005). McAdams has consulted and lectured about online journalism in Argentina, Canada, Europe, Hong Kong, Malaysia, Thailand and Vietnam. For eight months in 2004-2005, she was a Fulbright Scholar in Malaysia. Her M.A. is in media studies from The New School for Social Research, New York, and her B.A. is in print journalism from Penn State. Address: Address -3049
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- Authors
- Armstrong, C. L., & McAdams, M. J.
- Affiliations
- University of Florida (US)
- ORCID
- Armstrong, Cory L.
- Venue
- Journal of Computer-Mediated Communication
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-04
- Volume
- 14
- Issue
- 3
- Pages
- 435-456
- ISSN
- 1083-6101 (ISSN-L)
- OpenAlex
- W1969812592
- Cited by
- 179
- References
- 54
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 3 · 2023: 11 · 2022: 11 · 2021: 15 · 2020: 22 · 2019: 23 · 2018: 8 · 2017: 10 · 2016: 6 · 2015: 11 · 2014: 6 · 2013: 12 · 2012: 10
- FWCI
- 37.88
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Computer-Mediated Communication (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › Knowledge Management and Sharing
- Keywords
- gender cues, perceived credibility, bloggers, author gender, information seekers, personal motivation, gender stereotypes, online information seeking
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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