Trust Necessitated through Metrics: Estimating the Trustworthiness of Websites☆

The issue of trust is of exhilarating concern in case of information disseminated through websites. Digitization technologies such as Internet has lowered the cost and increased the access to information of all kinds. This increased exposure to information from humongous number of websites poses a need for some mechanism or tool that can address this issue and provide rankings to the websites on basis of their credibility or the trust value they possess. Previous research has shown a lot of efforts in this area. Both exogenous and endogenous signals have been evaluated to derive the credibility of websites. Trust being more of a sociological virtue of psychometric nature; cannot be quantified easily. Aiming this fact we have tried to measure the trust by evaluating the actual behavioral metrics of the users (of the websites) which gets collected by analytical tools automatically with every hit on a website. This gives a pertinent and bias-free quantification of trust value of a website as tools collect the data being anonymous from the user. In this paper, we have introduced our novel web-based tool which estimates trust (of websites) imposed by web metrics collected through similarweb.com. The tool will re-rank the web-links (URLs) extracted from Google search engine for any keyword according to the trust maintained by the actual users of the websites. We will also evaluate the performance of our tool in terms of validated rankings and benchmarking it with other recently acceptable tools.

[1]  K. Freeman,et al.  An Examination of Factors That Affect the Credibility of Online Health Information , 2004 .

[2]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[3]  Jan Maarten Schraagen,et al.  The role of topic familiarity in online credibility evaluation support , 2012 .

[4]  Shruti Kohli,et al.  Escalation of TRUST analysis in web , 2015, Conf. Computing Frontiers.

[5]  Miriam J. Metzger.  Making sense of credibility on the Web: Models for evaluating online information and recommendations for future research , 2007 .

[6]  Herre van Oostendorp,et al.  An Attempt to Automate the Process of Source Evaluation , 2011 .

[7]  Sadie Creese,et al.  Two sides of the coin: measuring and communicating the trustworthiness of online information , 2014, Journal of Trust Management.

[8]  Susan Wiedenbeck,et al.  On-line trust: concepts, evolving themes, a model , 2003, Int. J. Hum. Comput. Stud..

[9]  Ronald E. Rice,et al.  The internet and health communication : experience and expectations , 2001 .

[10]  Matthijs L. Noordzij,et al.  Topic familiarity and information skills in online credibility evaluation , 2013, J. Assoc. Inf. Sci. Technol..

[11]  Henriette Cramer,et al.  The effects of source credibility ratings in a cultural heritage information aggregator , 2009, WICOW.

[12]  Barbara Rosario,et al.  What is disputed on the web? , 2010, WICOW '10.

[13]  J. Powell,et al.  Empirical studies assessing the quality of health information for consumers on the world wide web: a systematic review. , 2002, JAMA.

[14]  Shruti Kohli and Himani Singal.  A Methodological Approach for Quantizing Trust from Human Behavior for Content-Driven Websites , 2015 .

[15]  Jan Maarten Schraagen,et al.  The influence of source cues and topic familiarity on credibility evaluation , 2013, Comput. Hum. Behav..

[16]  B. J. Fogg,et al.  The elements of computer credibility , 1999, CHI '99.

[17]  Janet Morahan-Martin,et al.  Information and Misinformation Online: Recommendations for Facilitating Accurate Mental Health Information Retrieval and Evaluation , 2000, Cyberpsychology Behav. Soc. Netw..

[18]  Wendy Hall,et al.  Trustworthiness criteria for supporting users to assess the credibility of web information , 2013, WWW '13 Companion.

[19]  Shruti Kohli,et al.  Conceptual model for obfuscated TRUST induced from web analytics data for content-driven websites , 2014, 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[20]  Karl Aberer,et al.  Web Credibility: Features Exploration and Credibility Prediction , 2013, ECIR.

[21]  ChengXiang Zhai,et al.  Reliability Prediction of Webpages in the Medical Domain , 2012, ECIR.

[22]  Jan Maarten Schraagen,et al.  Trust in wikipedia: how users trust information from an unknown source , 2010, WICOW '10.

[23]  Bipin Indurkhya,et al.  Providing Web Credibility Assessment Support , 2014, ECCE.

[24]  Huan Liu,et al.  A tool for collecting provenance data in social media , 2013, KDD.

[25]  Manish Latthe,et al.  Accuracy of information on apparently credible websites: survey of five common health topics , 2002, BMJ : British Medical Journal.