The Psychological Appeal of Personalized Content in Web Portals: Does Customization Affect Attitudes and Behavior?
Abstract
Internet technology has made possible the widespread dissemination of individualized media messages, but we know very little about their psychological import. A between-subjects experiment ( N =60) with three levels of customization (low, medium, high) was designed to examine whether greater levels of personalized content engender more positive attitudes. The results not only confirm this hypothesis but also reveal the mediating role played by users’ perceptions of relevance, involvement, interactivity, and novelty of portal content. In addition, customization has behavioral effects in that it affects users’ browsing activity.
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The impact of novelty (bias resulting from perceived "new" or "innovative" technology) exists.
“the impact of novelty (ie, bias resulting from perceived “new” or “innovative” technology [86])”
From eMental Healthcare Technologies for Anxiety and Depression in Childhood and Adolescence: Systematic Review of Studies Reporting Implementation Outcomes (2018) · cites this paper as [86]
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- Authors
- Kalyanaraman, S., & Sundar, S. S.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Pennsylvania State University (US)
- ORCID
- Sundar, S. Shyam
- Venue
- Journal of Communication
- Publisher
- Oxford University Press (OUP)
- Published
- 2006-03-01
- Volume
- 56
- Issue
- 1
- Pages
- 110-132
- ISSN
- 0021-9916 (ISSN-L)
- 1460-2466
- OpenAlex
- W2034182670
- Cited by
- 475
- References
- 65
- Citations by year
- 2026: 15 · 2025: 23 · 2024: 24 · 2023: 43 · 2022: 31 · 2021: 27 · 2020: 54 · 2019: 62 · 2018: 28 · 2017: 15 · 2016: 22 · 2015: 28 · 2014: 22 · 2013: 23 · 2012: 14
- FWCI
- 8.47
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Communication (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Media and Digital Communication
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
- Keywords
- content personalization, web portal, customization, user attitudes, user behavior, perceived relevance, user participation, interactivity, novelty, browsing behavior
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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