DIGITAL RUMORS, COGNITIVE TRUST, AND NEWS VERIFICATION BEHAVIOR: A QUANTITATIVE ASSESSMENT OF FAKE NEWS CONSUMPTION AMONG JOURNALISM STUDENTS IN DELHI-NCR UNIVERSITIES

Authors

  • Anurag Kumar Mishra Research Scholar Department of Journalism and Mass Communication IFTM University Moradabad
  • Dr. Rajesh Kumar Shukla PhD Supervisor & Head Department of Journalism and Mass Communication School of Education and Humanities IFTM University Moradabad
  • Dr. Ramesh Kumar Sharma PhD Co- Supervisor &- Professor, VSJMC Vivekananda Institute of Professional Studies-TC, Delhi

DOI:

https://doi.org/10.29121/shodhkosh.v7.i12s.2026.8344

Keywords:

Fake News, Cognitive Trust, News Verification, Journalism Students, Digital Rumors, Media Literacy, Peer Influence, Delhi-Ncr, Misinformation Acceptance, Social Media Dependency

Abstract [English]

Cognitive and behavioral reactions to fake news by journalism students is a little-studied aspect of media literacy scholarship, especially in a time when fake news is proliferating and increasingly pervasive. This study is a quantitative analysis of the interaction of fake news exposure, digital rumors consumption, cognitive trust formation, peer influence, social media dependency, and digital literacy in influencing news verification behavior among journalism and mass communication (JMC) students at Delhi-NCR universities. Primary data was collected from N = 500 journalism students studying at Jamia Millia Islamia Delhi University, Delhi; Guru Gobind Singh Indraprastha University, Delhi and Amity University, Noida that was sampled using stratified random sampling procedure. Data was collected from a questionnaire consisting of 50 items which were validated using SPSS v.26. Pearson's correlation, multiple regression analysis, one-way ANOVA, independent sample t-tests, and Chi-square tests were used. Constructs achieved a range of Cronbach's Alpha coefficients between 0.80 and 0.91, which suggests reliability of the instrument. Results indicated that the highest predictors of misinformation acceptance were cognitive trust in social media (β = 0.49, p < .001), and the highest predictors of news verification behavior were digital literacy (β = −0.44, p < .001). Peer influence had a significant moderation effect on the association between fake news exposure and verification intention. This revealed significant differences between post and undergraduate levels in terms of the rigor of verification (t = 4.87, p < .001). There was a significantly different level of digital literacy across the universities (F = 9.21, p < .001). The findings of the study have empirical value for the field of journalism education as well as have suggestions for journalism education curriculum in India to inculcate the culture of verification.

References

Ashley, S., Poepsel, M., & Willis, E. (2017). Media literacy and news credibility: Does knowledge of media ownership increase skepticism in news consumers? Journal of Media Literacy Education, 9(2), 1–22. https://doi.org/10.23860/JMLE-2017-09-02-01

Bakshy, E., Messing, S., & Adamic, L. A. (2015). Exposure to ideologically diverse news and opinion on Facebook. Science, 348(6239), 1130–1132. https://doi.org/10.1126/science.aaa1160 DOI: https://doi.org/10.1126/science.aaa1160

Ball-Rokeach, S. J., & DeFleur, M. L. (1976). A dependency model of mass-media effects. Communication Research, 3(1), 3–21. https://doi.org/10.1177/009365027600300101 DOI: https://doi.org/10.1177/009365027600300101

Caulfield, M. (2019). SIFT (The four moves). Hapgood. https://hapgood.us/2019/06/19/sift-the-four-moves/

Cochran, W. G. (1977). Sampling techniques (3rd ed.). John Wiley & Sons.

Craft, S., Ashley, S., & Maksl, A. (2016). Elements of media literacy are associated with online news credibility assessments. Atlantic Journal of Communication, 24(4), 217–226. https://doi.org/10.1080/15456870.2016.1209320

DeVellis, R. F. (2017). Scale development: Theory and applications (4th ed.). SAGE Publications.

Diddi, A., & LaRose, R. (2006). Getting hooked on news: Uses and gratifications and the formation of news habits among college students in an internet environment. Journal of Broadcasting & Electronic Media, 50(2), 193–210. https://doi.org/10.1207/s15506878jobem5002_2 DOI: https://doi.org/10.1207/s15506878jobem5002_2

Edgerly, S., & Vraga, E. K. (2020). News, non-news, and the hybrid news environment. Journalism, 21(9), 1199–1215. https://doi.org/10.1177/1464884917730709 DOI: https://doi.org/10.1177/1464884917730709

Festinger, L. (1957). A theory of cognitive dissonance. Stanford University Press. DOI: https://doi.org/10.1515/9781503620766

Flanagin, A. J., & Metzger, M. J. (2020). Big data and the threat to information quality: Online credibility as a product of collective intelligence. In M. Zimdars & K. McLeod (Eds.), Fake news: Understanding media and misinformation in the digital age (pp. 71–84). MIT Press.

Fletcher, R., & Nielsen, R. K. (2018). Are news audiences increasingly fragmented? A cross-national comparative analysis of cross-platform news audience fragmentation and duplication. Journal of Communication, 67(4), 476–498. https://doi.org/10.1111/jcom.12315 DOI: https://doi.org/10.1111/jcom.12315

Gerbner, G., Gross, L., Morgan, M., & Signorielli, N. (1986). Living with television: The dynamics of the cultivation process. In J. Bryant & D. Zillmann (Eds.), Perspectives on media effects (pp. 17–40). Lawrence Erlbaum Associates.

Graves, L. (2016). Deciding what's true: The rise of political fact-checking in American journalism. Columbia University Press. DOI: https://doi.org/10.7312/grav17506

Guess, A. M., Lerner, M., Lyons, B., Montgomery, J. M., Nyhan, B., Reifler, J., & Sircar, N. (2020). A digital media literacy intervention increases discernment between mainstream and false news in the United States and India. Proceedings of the National Academy of Sciences, 117(27), 15536–15545. https://doi.org/10.1073/pnas.1920498117 DOI: https://doi.org/10.1073/pnas.1920498117

Hameleers, M., Powell, T. E., Van Der Meer, T. G. L. A., & Bos, L. (2021). A picture paints a thousand lies? The effects and mechanisms of multimodal disinformation and rebuttals disseminated via social media. Political Communication, 38(1–2), 281–301. https://doi.org/10.1080/10584609.2020.1795286 DOI: https://doi.org/10.1080/10584609.2019.1674979

Hayes, A. F. (2022). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (3rd ed.). Guilford Press.

IBM Corp. (2021). IBM SPSS Statistics for Windows, Version 26.0. IBM Corp.

Indian Council of Social Science Research. (2021). ICSSR research ethics policy. Government of India.

Johnson, T. J., & Kaye, B. K. (2014). Credibility of social network sites for political information among politically interested internet users. Journal of Computer-Mediated Communication, 19(4), 957–974. https://doi.org/10.1111/jcc4.12084 DOI: https://doi.org/10.1111/jcc4.12084

Kumar, S., & Singh, P. (2023). Emotional Appeal in the Tweets: A Study on Indian National Political Parties. Journal of Communication and Management, 2(02), 95–97. https://doi.org/10.58966/JCM2023223 DOI: https://doi.org/10.58966/JCM2023223

Downloads

Published

2026-05-26

How to Cite

Mishra, A. K., Shukla, R. K., & Sharma, R. K. (2026). DIGITAL RUMORS, COGNITIVE TRUST, AND NEWS VERIFICATION BEHAVIOR: A QUANTITATIVE ASSESSMENT OF FAKE NEWS CONSUMPTION AMONG JOURNALISM STUDENTS IN DELHI-NCR UNIVERSITIES. ShodhKosh: Journal of Visual and Performing Arts, 7(12s), 169–183. https://doi.org/10.29121/shodhkosh.v7.i12s.2026.8344