What affects web credibility perception? An analysis of textual justifications

Authors

  • Michał Kąkol Polish-Japanese Academy of Information Technology, Warsaw
  • Radosław Nielek Polish-Japanese Academy of Information Technology, Warsaw

DOI:

https://doi.org/10.7494/csci.2015.16.3.295

Keywords:

credibility, world wide web, credibility ratings, reliability, credibility assessment heuristics, credibility evaluation factors

Abstract

In this paper, we present the findings of a qualitative analysis of 15,750 comments left by 2,041 participants in a Reconcile web credibility evaluation study. While assessing the credibility of the presented pages, respondents of the Reconcile studies were also asked to justify their ratings in writing. This work attempts to give an insight into the factors that affected the credibility assessment. To the best of our knowledge, the presented study is the most-recent large-scale study of its kind carried out since 2003, when the Fogg et al. How do users evaluate the credibility of Web sites? A study with over 2,500 participants’ paper was published. The performed analysis shows that the findings made a decade ago are still mostly valid today despite the passage of time and the advancement of Internet technologies. However we report a weaker impact of webpage appearance. A much bigger dataset (as compared to Fogg’s studies) allowed respondents to reveal additional features, which influenced the credibility evaluations.

Downloads

Download data is not yet available.

References

Borzymek P., Sydow M., Wierzbicki A.: Enriching trust prediction model in social network with user rating similarity. In: Computational Aspects of Social Networks, 2009. CASON’09. International Conference on, pp. 40–47, IEEE, 2009.

Diefenbach D. L.: Historical Foundations of Computer-Assisted Content. Theory, method, and practice in computer content analysis, vol. 16, p. 13, 2001.

Flanagin A. J., Metzger M. J.: The role of site features, user attributes, and information verification behaviors on the perceived credibility of web-based information. New Media & Society, vol. 9(2), pp. 319–342, 2007.

Fogg B., Soohoo C., Danielson D.R., Marable L., Stanford J., Tauber E.R.: How do users evaluate the credibility of Web sites?: a study with over 2,500 participants. In: Proceedings of the 2003 conference on Designing for user experiences, pp. 1–15, ACM, 2003.

Kaszuba T., Hupa A., Wierzbicki A.: Advanced feedback management for internet auction reputation systems. Internet Computing, IEEE, vol. 14(5), pp. 31–37, 2010.

Metzger M. J., Flanagin A. J., Medders R. B.: Social and heuristic approaches to credibility evaluation online. Journal of Communication, vol. 60(3), pp. 413–439, 2010.

Morzy M., Wierzbicki A.: The sound of silence: Mining implicit feedbacks to compute reputation. In: Internet and Network Economics, pp. 365–376, Springer, Berlin, Heidelberg, 2006.

O’Donovan J., Kang B., Meyer G., Hollerer T., Adalii S.: Credibility in context: An analysis of feature distributions in twitter. In: Privacy, Security, Risk and Trust (PASSAT), 2012 International Conference on and 2012 International Confernece on Social Computing (SocialCom), pp. 293–301, IEEE, 2012.

Rafalak M., Abramczuk K., Wierzbicki A.: Incredible: Is (Almost) All Web Content Trustworthy? Analysis of psychological factors related to website credibility evaluation. In: Proceedings of the companion publication of the 23rd international conference on World wide web companion, pp. 1117–1122, International World Wide Web Conferences Steering Committee, 2014.

Rafalak M., Bilski P., Wierzbicki A.: Analysis of Demographical Factors Influence on Websites Credibility Evaluation. In: Human-Computer Interaction. Applications and Services, pp. 57–68, Springer, International Publishing, 2014.

Scharkow M.: Automatische Inhaltsanalyse und maschinelles Lernen. epubli, 2012.

Shariff S. M., Zhang X., Sanderson M.: User Perception of Information Credibility of News on Twitter. In: Advances in Information Retrieval, pp. 513–518, Springer, International Publishing, 2014.

Stone P.: Improved Quality of Content Analysis Categories: Computerized Disambiguation Rules Forhigh Frequency English Words, presented at an National Conference on Content Analysis, 1967.

Wierzbicki A.: The case for fairness of trust management. Electronic Notes in Theoretical Computer Science, vol. 197(2), pp. 73–89, 2008.

Downloads

Published

2015-09-07

How to Cite

Kąkol, M., & Nielek, R. (2015). What affects web credibility perception? An analysis of textual justifications. Computer Science, 16(3), 295. https://doi.org/10.7494/csci.2015.16.3.295

Issue

Section

Articles

Most read articles by the same author(s)