Digital Information Credibility: Towards a Set of Guidelines for Quality Assessment of Grey Literature in Multivocal Literature Review
Source abstract
Abstract
Credibility, in general, can be interpreted as a sense of trust in someone. The credibility of information remarkably influences the public’s willingness to do or not to do some things. In this research study, the credibility of digital news stories can be interpreted as the sense of confidence a person has in a source of available information that affects their behavior. Humans spread less credible information instead of more credible information very quickly because humans take an interest in fear, disgust, and surprise. Less credible news may affect individuals as well as economies. Therefore, there is a dire need in the current digital era to find out what affects the credibility of digital news stories. This study aims to review the published literature and the grey literature to determine the factors affecting digital news credibility and the factors that build credibility in digital news stories. In this paper, we have developed a multivocal literature review protocol to assess the credibility of digital news stories. The multivocal literature review is an advanced version of the systematic literature review that searches for grey literature in addition to the published literature. The expected outcomes after implementing our protocol will be a list of credibility factors and their practices that can play a vital role in ensuring the credibility of digital news stories. Based on this protocol, we formulated guidelines for the quality assessment of grey literature. The future direction of this research is to analyze the factors through multi-criteria decision-making (MCDM), i.e., analytical hierarchical process.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Misinformation and Its Impacts · Information and Cyber Security · Big Data and Business Intelligence
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Computer Software Engineering, University of Engineering and Technology, Peshawar 25120, Pakistan
Department of Computer Software Engineering, University of Engineering and Technology, Mardan 23200, Pakistan
Department of Computer Science, University of Engineering and Technology, Mardan 23200, Pakistan
EIAS Data Science and Blockchain Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia
Funding
Prince Sultan University and EIAS Lab
References (50)
Show source-provided references
1. de Kunder, M. (2020, March 11). WorldWideWebSize. Available online: http://www.worldwideWebsize.com/.
2. Open archival information system (OAIS) reference model
3. A systematic approach towards Web preservation
4. Khan, M. (2018). Using Text Processing Techniques for Linking News Stories for Digital Preservation. [Ph.D. Thesis, Faculty of Computer Science].
5. Khan, M., Ur Rahman, A., and Daud Awan, M. (2018, January 25–26). Term-based approach for linking digital news stories. Proceedings of the Italian Research Conference on Digital Libraries, Udine, Italy.10.1007/978-3-319-73165-0_13 ↗
6. Khan, M., Rahman, A.U., Awan, M.D., and Alam, S.M. (2016, January 19–21). Normalizing digital news-stories for preservation. Proceedings of the 2016 Eleventh International Conference on Digital Information Management (ICDIM), Porto, Portugal.10.1109/ICDIM.2016.7829785 ↗
7. Khan, M., and Rahman, A.U. (2015, January 9–12). Digital news story preservation framework. Proceedings of the of Digital Libraries: Providing Quality Information: 17th International Conference on Asia-Pacific Digital Libraries, ICADL, Seoul, Republic of Korea.
8. What Is Credible Information
9. Fogg, B.J., Marshall, J., Laraki, O., Osipovich, A., Varma, C., Fang, N., Paul, J., Rangnekar, A., Shon, J., and Swani, P. (2001, January 1). What makes Web sites credible? A report on a large quantitative study. Proceedings of the of the SIGCHI Conference on Human Factors in Computing Systems, Seattle, DC, USA.10.1145/365024.365037 ↗
10. Gupta, A., Lamba, H., Kumaraguru, P., and Joshi, A. (2013, January 13–17). Faking sandy: Characterizing and identifying fake images on twitter during hurricane sandy. Proceedings of the of the 22nd International Conference on World Wide Web, Rio de Janeiro, Brazil.10.1145/2487788.2488033 ↗
11. Credibility in social media: Opinions, news, and health information—A survey10.1002/widm.1209 ↗
12. Rapoza, K. (Forbes News, 2017). Can ‘Fake News’ Impact The Stock Market?, Forbes News.
13. Mendoza, M., Poblete, B., and Castillo, C. (2010, January 25–28). Twitter under crisis: Can we trust what we RT?. Proceedings of the First Workshop on Social Media Analytics, Washington, DC, USA.10.1145/1964858.1964869 ↗
14. Starbird, K., Maddock, J., Orand, M., Achterman, P., and Mason, R.M. (2014). IConference 2014 Proceedings, iSchools. Available online: https://www.ideals.illinois.edu/items/47268.
15. A Maturity Model for Secure Software Design: A Multivocal Study10.1109/ACCESS.2020.3040220 ↗
16. Neto, G.T.G., Santos, W.B., Endo, P.T., and Fagundes, R.A. (2019, January 19–20). Multivocal literature reviews in software engineering: Preliminary findings from a tertiary study. Proceedings of the 2019 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), Porto de Galinhas, Brazil.10.1109/ESEM.2019.8870142 ↗
17. Guidelines for including grey literature and conducting multivocal literature reviews in software engineering10.1016/j.infsof.2018.09.006 ↗
18. Teaching undergrads WEB evaluation10.5860/crln.59.7.522 ↗
19. Rating health information on the Internet: Navigating to knowledge or to Babel?10.1001/jama.279.8.611 ↗
20. Is advertising believability really important?
21. Library and information resources and users of digital resources in the humanities10.1108/00330330810851555 ↗
22. Fogg, B.J., and Tseng, H. (1999, January 5–20). The elements of computer credibility. Proceedings of the of the SIGCHI Conference on Human Factors in Computing Systems, Pittsburgh, PA, USA.10.1145/302979.303001 ↗
23. Fogg, B.J., Soohoo, C., Danielson, D.R., Marable, L., Stanford, J., and Tauber, E.R. (2003, January 6–7). How do users evaluate the credibility of Web sites? A study with over 2500 participants. Proceedings of the 2003 Conference on Designing for User Experiences, San Francisco, CA, USA.10.1145/997078.997097 ↗
24. The influence of source credibility on communication effectiveness10.1086/266350 ↗
25. Web site credibility: Why do people believe what they believe?10.1007/s11251-008-9080-7 ↗
26. Stanford, J., Tauber, E.R., Fogg, B., and Marable, L. (2002). Experts vs. Online Consumers: A Comparative Credibility Study Of Health and Finance Web Sites, Consumer Web Watch.
27. Cheskin, R. (2000). Cheskin Research Report, OD Practioner.
28. Comprehension and perceived believability of seals of approval information in advertising10.1080/00913367.1993.10673407 ↗
29. Source vs. content effects on judgments of news believability
30. Believe it or not: Factors influencing credibility on the Web10.1002/asi.10016 ↗
31. Credibility and trust of information in online environments: The use of cognitive heuristics10.1016/j.pragma.2013.07.012 ↗
32. Mitchel, A. (2022, April 22). State of The News Media 2015. Available online: http://www.journalism.org/2015/04/29/state-of-the-news-media-2015.
33. Rubin, V.L., Conroy, N.J., and Chen, Y. (2015, January 5–8). Towards news verification: Deception detection methods for news discourse. Proceedings of the Hawaii International Conference on System Sciences, Kauai, Hawaii. Available online: https://sites.socsci.uci.edu/~lpearl/courses/readings/RubinEtAl2015_DeceptionDetectionNews.pdf.
34. Barriers of managing cloud outsource software development projects: A multivocal study10.1007/s11042-021-11245-9 ↗
35. Antil, P. (2020). Requirements engineering in global scaled agile software development environment: A multi-vocal literature review protocol. arXiv.
36. Lohrasbinasab, I., Acharya, P.B., and Colomo-Palacios, R. (2020, January 1–4). BizDevOps: A Multivocal Literature Review. Proceedings of the International Conference on Computational Science and Its Applications, Cagliari, Italy.10.1007/978-3-030-58817-5_50 ↗
37. Security in microservice-based systems: A multivocal literature review10.1016/j.cose.2021.102200 ↗
38. Nylund, A. (2020). A Multivocal Literature Review on Developer Experience. [Dissertation Thesis, School of Science, Aalto University]. Available online: https://aaltodoc.aalto.fi/handle/123456789/43567.
39. Data Plane Failure and Its Recovery Techniques in SDN: A Systematic Literature Review
40. Expedited Analytical Hierarchical Process for Multicriteria Decision Making
41. Langville, A.N., and Meyer, C.D. (2011). Google’s PageRank and Beyond, Princeton University Press.
42. A systematic review of search-based testing for non-functional system properties10.1016/j.infsof.2008.12.005 ↗
43. Systematic mapping study on security approaches in secure software engineering10.1109/ACCESS.2021.3052311 ↗
44. Quality assessment framework to rank software projects10.1007/s10515-022-00342-0 ↗
45. Farace, D.J. (2022, March 03). The 4th International Conference on Grey Literature, Washington, DC, USA, 4–5 October 1999. Available online: https://cds.cern.ch/record/403957?ln=en.
46. Guidelines for developing a systematic literature review for studies related to climate change adaptation10.1007/s11356-021-13178-0 ↗
47. Systematic literature reviews in software engineering—A systematic literature review10.1016/j.infsof.2008.09.009 ↗
48. Wohlin, C. (2014, January 13–14). Guidelines for snowballing in systematic literature studies and a replication in software engineering. Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering, London, UK.10.1145/2601248.2601268 ↗
49. Guidelines for conducting systematic mapping studies in software engineering: An update10.1016/j.infsof.2015.03.007 ↗
50. Petersen, K., Feldt, R., Mujtaba, S., and Mattsson, M. (2008, January 26–27). Systematic mapping studies in software engineering. Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering (EASE) 12, Swindon, UK.10.14236/ewic/EASE2008.8 ↗