The language of manipulation: A multimodal discourse analysis of mainstream news media and fake news websites

Martin Mikulas

Abstract


In the contemporary digital media landscape marked by the presence of disinformation and fake news, the aim of this study is to perform a comparative analysis of mainstream news media and fake news websites, and to identify the multimodal resources characteristic of them. In particular, the study focuses on newsbits and newsbites, which comprise clusters of headlines, leads, hyperlinks, and images (Knox 2007), because they arguably represent the most salient features of any news websites. A representative corpus of newsbits and newsbites was compiled from mainstream news media and fake news websites that meet the criteria of such websites defined in the study. In total, 8 newsbites and newsbits were collected from 2 mainstream news media and 2 fake news websites. The study primarily draws on Bednarek and Caple’s (2012) approach to news discourse, which affords ways to perform a complex multimodal analysis of text and image, as well as explores the concepts of news values, parameters of evaluation, text-image relations, and communicative functions of images. As the primary objective of newsbits and newsbites is to entice readers to read the full article, the creation of compelling newsbits and newsbites is the shared goal of both mainstream news media and fake news websites, even though their broader objectives or ethical standards may not align. The manipulative impact of linguistic modes is more pronounced in the case of fake news websites because they rely on attracting clicks through controversial evaluations or alternate perspectives of some existing news. On the other hand, mainstream news media create more engaging and clickable newsbits and newsbites with higher emotional pull via the interplay of text and real-life images.


Keywords


mainstream media; fake news; comparative analysis; newsbits; newsbites; news values; evaluation

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References


Ackland, R., and K. Gwynn. 2021. "Truth and the Dynamics of News Diffusion on Twitter."

In The Psychology of Fake News: Accepting, Sharing, and Correcting Misinformation, edited by R. Greifeneder, M. Jaffé, E. Newman, and N. Schwarz, 27-45. New York: Routledge.

Bednarek, M., and H. Caple. 2012. News Discourse. New York: Continuum.

Bell, A. 1991. The Language of News Media. Wiley-Blackwell.

Greifeneder, R., Mariela E., Jaffé E., Eryn J., Schwarz N. 2021. "What is New and True

About Fake News?" In The Psychology of Fake News: Accepting, Sharing, and

Correcting Misinformation, edited by R. Greifeneder et al., 1-6. 1st ed. Routledge.

Holt, K., and L. Frischlich. 2019. "Key Dimensions of Alternative News Media." Digital

Journalism 7, no. 7: 860-869. doi:10.1080/21670811.2019.1625715.

Hughes, H. M. 1980. News and the Human Interest Story. Routledge.

Knox, J. S. 2007. "Visual-Verbal Communication on Online Newspaper Home Pages." Visual

Communication 6, no. 1: 19-53.

Mineshima, Michio. “Discourse Analysis of News Texts by the Application of Systemic

Functional Grammar.” (2009).

Molina, M. D., S. S. Sundar, E. Tandoc, and D. Lee. 2021. "‘Fake News’ Is Not Simply False

Information: A Concept Explication and Taxonomy of Online Content." American

Behavioral Scientist 65, no. 2: 180–212. doi:10.1177/0002764219878224.

Rau, C. 2010. Dealing with the Media. Sydney: University of New South Wales Press.

Wimmer, R. D., and J. R. Dominick. 2014. Mass Media Research: An Introduction. 10th ed.

Boston: Wadsworth, Cengage Learning.

Yoon, S., Park, K., Shin, J., Lim, H., Won, S., Cha, M., and Jung, K. 2019. "Detecting

Incongruity between News Headlines and Body Text via Deep Hierarchical Encoder."

In The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), 791-800.




DOI: http://dx.doi.org/10.17951/nh.2024.9.43-59
Date of publication: 2024-12-30 19:41:36
Date of submission: 2024-02-19 18:08:03


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