معرفی و بررسی انطباقی مدلهای ارزیابی اعتبار وب

نویسندگان
دانشگاه فردوسی مشهد
چکیده
زمینه و هدف: از آنجا که هر کسی میتواند هر نوع اطلاعاتی را در فضای مجازی آزادانه و بدون نیاز به هر نوع مجوزی، انتشار دهد و هیچگونه مسئولیتی را در قبال صحت و درستی آن نمیپذیرد، پالایش اطلاعات معتبر از نامعتبر اهمیتی چند مییابد. در این مقاله، ضمن بررسی مفهوم اعتبار، به توصیف و تحلیل برخی از مدلهای شناخته شده و مطرح ارزیابی اعتبار وب، پرداخته میشود.

روش پژوهش: این پژوهش از بعد روش شناسی تحقیق، مروری و از منظر هدف، نظری است. همچنین گردآوری دادهها به روش مطالعه اسنادی صورت گرفته است.

یافته­ ها: تحلیل و ارزیابی مدلهای شناخته شده و مطرح اعتبار وب نظیر برجستگی-تفسیر فاگ، واتن و برکل برای چگونگی قضاوت اعتبار اطلاعات برخط، چارچوب یکپارچه ارزیابی اعتبار هیلیگاس و ریه، مدل MAIN ساندار، پردازش دوگانه متسگر، مدل 3S بازبینی شده لوکاسن و همکاران و چارچوب ارزیابی اعتبار چوی، نشان میدهد مفهومسازی نظاممند از ارتباط میان بعدهای کلیدی اعتبار و معیارهایی که میتوان آنها را در ارزیابی اعتبار وب مورد استفاده قرار داد در هیچ یک از این مدلها غیر از مدل چوی، وجود ندارد و به این علت این مدلها و نظریهها قدرت تبیینی محدودی برای تفسیر جامع و منسجم از یافتههای حاصل از مطالعه­های تجربی دارند.

نتیجه ­گیری: به دلیل عدم بررسی تجربی این چارچوبهای نظری با ابزاری استاندارد در مقیاس وسیع، هیچیک از پشتوانه تجربی برخوردار نیستند؛ بنابراین ضروری است تا پژوهشگران تلاش نموده تا پژوهشهای تجربی زیادی در این زمینه انجام دهند و اعتبار هر یک از این چارچوبهای نظری را با ارائه پشتوانه تجربی ارتقاء دهند.



کلیدواژه‌ها: بعدهای کلیدی اعتبار، ارزیابی اعتبار وب، اعتبار اطلاعات، کیفیت اطلاعات، ابزار استاندارد
کلیدواژه‌ها

عنوان مقاله English

Introduction and a Comparative Analysis of Web Credibility Assessment Models

نویسندگان English

Hedayat Behroozfar
Azam Sanatjoo
Mohsen Nokarizi
Ferdowsi University of Mashhad
چکیده English

Background and Aim: Since anyone can freely share any kinds of information in the cyberspace almost without authenticity, validation information seems important. This paper examines the concept of credibility and describes and analyzes some well-known models for the evaluation of the Web credibility.

Methods: This research is a review in terms of research methodology and theoretical in terms of the goal. Data collection was using documentary method.

Results: The assessment of known models of Web Credibility including prominence-interpretation theory of Fogg, Wathen and Burkell’s model for how users judge the credibility of on-line information, Hilligoss and Rieh’s unifying framework of credibility, Sundar’s MAIN model, Metzger’s dual processing model of credibility assessment, Lucassen et al.’s revised 3S-model of credibility, and Choi new framework for web credibility showed that the systematic concept of the connection between credit key dimensions and criteria that can be used to assess the credibility of the Web exists in none of these models other than Choi and thus the templates and the theories have limited explanatory power for a comprehensive interpretation of findings of experimental studies.

Conclusion: Due to lack of imperical testing of these theoretical frameworks through standard tools on a large scale, no one was empirically supported. Thus, it is necessary to examine these frameworks empirically to improve their validity with an experimental basis.

کلیدواژه‌ها English

Model
Web credibility Assessment
Information credibility
Information Quality
Standard Tool
Alexander, J. E.; Tate, M. A. (1999). Web wisdom: How to Evaluate and Create Information Quality on the Web. Mahwah, NJ: Erlbaum.
Beck, S. E. (1997). The good, the bad & the ugly, or, why it’s a good idea to evaluate web sources. Re-trieved May 13, 2016, from www.ucolick.org/~max/Astro18-2014/GoodBadUgly.pdf
Choi, W. (2015). A New framework of web credibility assessment and an exploratory study of older adults’ information behavior on the web. Un-published doctoral dissertation, Florida state uni-versity, Florida.
Cool, C., Belkin, N. J., Frieder, O., & Kantor, P. (1993). Characteristics of texts affecting relevance judg-ments. Proceedings of the 14th National Online Meeting.
Credibility. (2011). In Oxford Advanced American dictionary for learners of English. China: Oxford University Press.
Flanagin, A. J.; Metzger, M. J. (2008). Digital media and youth: Unparalleled opportunity and unprec-edented responsibility. In M. J. Metzger, & A. J. Flanagin (Eds.), Digital media,youth, and credibil-ity (pp. 5-27). Cambridge, MA: The MIT Press.
Fogg, B.; Tseng, H. (1999). The elements of computer credibility. In Proceedings of the SIGCHI Confer-ence on Human factors in Computing Systems: the CHI is the Limit, May 15-20, 1999, Pittsburgh, Pennsylvania, USA (pp. 80-87). New York, NY: ACM.
Fogg, B. J. (2003a). Persuasive technology: Using computers to change what we think and do. San Francisco, CA: Morgan Kaufmann Publishers.
Fogg, B. J. (2003b). Prominence-interpretation theory. In G. Cockton, & P. Korhonen (Eds.),CHI '03 Ex-tended Abstracts on Human Factors in Compu-ting Systems (pp. 722-723).New York, NY: ACM.
Harris, R. (1997). Evaluating internet research sources. Retrieved May 13, 2016, from http://www.virtualsalt.com/evalu8it.html
Hilligoss, B., & Rieh, S. Y. (2008). Developing a unify-ing framework of credibility assessment: Con-struct, heuristics, and interaction in context. In-formation Processing & Management,44(4), 1467-1484.
Hong, T. (2006). The influence of structural and mes-sage features on Web site credibility. Journal of the American Society for Information Science and Technology, 57(1), 114-127.
Jessen, J.; Jørgensen, A. H. (2012). Aggregated trust-worthiness: Redefining online credibility through social validation. First Monday, 17(1).
Julien, H., & Barker, S. (2009). How high-school stu-dents find and evaluate scientific information: A basis for information literacy skills development. Library & Information Science Research, 31(1), 12-17.
Liu, Z. (2004). Perceptions of credibility of scholarly information on the Web. Information Processing & Management, 40, 1027-1038.
Liu, L.; Chi, L. (2002). Evolutional data quality: a theory-specific view. In International Conference on Information Quality, (ICIQ-02). Proceedings of the Seventh International Conference on Infor-mation Quality, Nov. 8-10, (292-304). Retrieved April 10, 2016, from http://mitiq.mit.edu/ICIQ/Documents/IQ%20Confer-ence%202002/Papers/EvolutionalDataQualityATheorySpecificView.pdf
Lucassen, T., Muilwijk, R., Noordzij, M. L., & Schraa-gen, J. M. (2013). Topic familiarity and infor-mation skills in online credibility evaluation. Jour-nal of the American Society for Information Sci-ence and Technology, 64(2), 254-264.
Lucassen, T., & Schraagen, J. M. (2011). Factual ac-curacy and trust in information: The role of exper-tise. Journal of the American Society for Infor-mation Science and Technology, 62(7), 1232-1242.
Metzger, M. J. (2007). Making sense of credibility on the Web: Models for evaluating online infor-mation and recommendations for future research. Journal of the American Society for Information Science and Technology, 58(13), 2078-2091.
Naumann, F.; Rolker, C. (2000). Assessment methods for information quality criteria. In Proceedings of the 2000 Conference on Information Quality. Proceedings of the fifth International Conference on Information Quality, October 20-21, (148-162). Retrieved March 15, 2016, from http://mitiq.mit.edu/ICIQ/iqpapers.aspx?iciqyear=2000
Razzaghi, A. (2002). Theories of social communica-tion. Tehran: Peykan. (Persian)
Rieh, S. Y.; Belkin, N. J. (1998). Understanding judg-ment of information quality and cognitive author-ity in the WWW. Proceedings of the American So-ciety for Information Science, 35, 279-289.
Rieh, S. Y.; Kim, Y.-M.; Yang, J. Y. & St. Jean, B. (2010). A diary study of credibility assessment in everyday life information activities on the web: Preliminary findings. Proceedings of the American Society for Information Science and Technology, 47(1), 1-10.
Shah, A. A., Ravana, S. D., Hamid, S., Ismail, M. A. (2015). Web credibility assessment: affecting fac-tors and assessment techniques. Information Re-search, 20(1), paper 655 Retrieved from http://InformationR.net/ir/20- 1/paper655.html
Song, J.; Zahedi, F. M. (2007). Trust in health info-mediaries. Decision Support Systems, 43 (2), 390-407.
Stvilia, B.; Twidale, M. B.; Smith, L. C. & Gsdrt, L. (2005). Assessing information quality of a com-munity-based encyclopedia. In International Conference on Information Quality. Proceeding of 10th International Conference on Information Quality., Nov. 4-6, (423-436). Retrieved May 5, 2016, from http://mitiq.mit.edu/iciqpapers.aspx?iciqyear=2005
Stvilia, B.; Gasser, L.; Twidale, M. B. & Smith, L. C. (2007). A framework for information quality as-sessment. Journal of the American Society for In-formation Science and Technology, 58(12), 1720-1733.
Sundar, S. S. (2008). The MAIN model: A heuristic approach to understanding technology effects on credibility. In M. J. Metzger, & A. J. Flanagin (Eds.), Digital media, youth, and credibility (pp. 73-100). Cambridge, MA: The MIT Press.
Wathen, C. N., & Burkell, J. (2002). Believe it or not: Factors influencing credibility on the Web. Journal of the American Society for Information Science and Technology, 53(2), 134-144.
Wilson, P. (1983). Second-hand knowledge: An in-quiry into cognitive authority. Westport, CT: Creenwood Press.
Zuh, X.; Gauch, S. (2000). Incorporating quality met-rics in centralized/distributed information retrieval on the World Wide Web. In Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information re-trieval. 23rd ACM International SIGIR Confer-ence on Research and Development in Infor-mation Retrieval, July 24-28, (288-295). New York: ACM (Association for Computing Machin-ery).