The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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]
Citations
Cites
The Handbook of Social Psychology
Gravatt, A. E., Lindzey, G. E., & Aronson, F. (1969) · The Family Coordinator · doi:10.2307/582242 · Cited by 12,518
DeLamater, J., & Ward, A. (2013) · Handbooks of sociology and social research · doi:10.1007/978-94-007-6772-0 · Cited by 7,590
Individualism and Collectivism
Hayek, F. A. (1976) · Routledge eBooks · doi:10.4324/9780203991718-8 · Cited by 6,060
Communication and Persuasion: Central and Peripheral Routes to Attitude Change
Marquart, F., & Naderer, B. (2015) · Springer eBooks · doi:10.1007/978-3-658-09923-7_20 · Cited by 5,011
Mass customization: The new frontier in business competition
Pine, B. J. (1999) · Journal of Manufacturing Systems · doi:10.1016/s0278-6125(99)90108-5 · Cited by 2,316
The Impact of Television Advertising: Learning Without Involvement
Krugman, H. E. (1965) · Public Opinion Quarterly · doi:10.1086/267335 · Cited by 1,570
The effect of severity of initiation on liking for a group.
Aronson, E., & Mills, J. (1959) · The Journal of Abnormal and Social Psychology · doi:10.1037/h0047195 · Cited by 1,297 · cited 1×
“Membership refers to the feeling that individuals have devoted a part of themselves to become a member and therefore believe that they have a certain entitlement to belong ( Aronson & Mills, 1959 ).”
BackgroundEmerging Theories in Health Promotion Practice and Research
DiClemente, R. J., Crosby, R. A., & Kegler, M. C. (2002) · Cited by 1,244
Postdecision changes in the desirability of alternatives.
Brehm, J. W. (1956) · Journal of Abnormal & Social Psychology · doi:10.1037/h0041006 · Cited by 1,109
Tailored and Targeted Health Communication: Strategies for Enhancing Information Relevance
Kreuter, M. W., & Wray, R. J. (2003) · American Journal of Health Behavior · doi:10.5993/ajhb.27.1.s3.6 · Cited by 1,095
Research works printed but not linked: 8
- 2002, Building a better mousetrap: Personalized start pages, USA Today
- 1985, The impact of uncertainty and insufficient resources in intergroup bias, Gedrag: Tijdschift voor Psychologic, 13, 29
- R. N. Katz & Associates, 2002, Web portals and higher education: Technologies to make IT personal, 1
- 2002, Web portals and higher education: Technologies to make IT personal
- 1999, “Mass customization” is not an oxymoron, Journal of Advertising Research, 39, 70
- 2000, Proceedings of the International Conference on E-Commerce and Web Technologies, 165
- 2001, E-commerce
- 1989, Predicting attention and memory for TV commercials using relevance, originality and impact scores
Cited by
Sorted by citations
Preacher, K. J., & Hayes, A. F. (2008) · Behavior Research Methods · doi:10.3758/brm.40.3.879 · Cited by 34,117
Statistical mediation analysis with a multicategorical independent variable
Hayes, A. F., & Preacher, K. J. (2014) · British Journal of Mathematical and Statistical Psychology · doi:10.1111/bmsp.12028 · Cited by 3,403
Understanding the appeal of user-generated media: a uses and gratification perspective
Shao, G. (2009) · Internet Research · doi:10.1108/10662240910927795 · Cited by 1,162
Kang, K., Lu, J., Guo, L., & Wen-Lu, L. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102251 · Cited by 740
Personalization versus Customization: The Importance of Agency, Privacy, and Power Usage
Sundar, S. S., & Marathe, S. S. (2010) · Human Communication Research · doi:10.1111/j.1468-2958.2010.01377.x · Cited by 588
Self-citation
Metadata
- 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
- Social Sciences › Communication › Media and Digital Communication
- Social Sciences › Business, Management and Accounting › Marketing › 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 ›
Are you an author, or do you see a problem with this page? Request a review
