Representing Trust in Digital Journalism

Author:

Coatney CarynORCID

Abstract

This article examines how journalists at two prominent news organizations have aimed to portray trustworthy digital reporting of marginalized communities. The case study draws on the concepts of engagement and trust as a resource to evaluate journalists’ articles and the related audience comments on<em> The New York Times</em> and <em>The Washington Post</em> digital sites. This study analyzed the digital news articles and audience comments in 2012 and the latter half of 2022 during the rapid expansion of mobile audiences and American readers’ declining trust in newspapers. As this study discovered, journalists at the two legacy organizations have portrayed novel forms of reporting relating to fresh notions of enhancing readers’ trust as well as elements of transparency and interactivity in the news. They have represented trustworthy journalism based on an inclusive approach and personalized depictions of marginalized communities’ experiences to appeal to readers increasingly using mobile devices. Although the journalists’ stories attracted some toxic tweets, their articles also encouraged digital subscribers’ loyalty and enthusiasm to help solve the reported problems affecting marginalized communities. This study indicates the possibilities of fostering trustworthy interactions among journalists and engaged subscribers in digital news spaces.

Publisher

Cogitatio

Subject

Communication

Reference76 articles.

1. 2012: The year in graphics. (2012, December 30). The New York Times. https://archive.nytimes.com/www.nytimes.com/interactive/2012/12/30/multimedia/2012-the-year-in-graphics.html

2. Alieva, I. (2023). How American media framed 2016 presidential election using data visualization: The case study of The New York Times and The Washington Post. Journalism Practice, 17(4), 814–840. https://www.tandfonline.com/doi/epub/10.1080/17512786.2021.1930573

3. Ananny, M., & Crawford, K. (2018). Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability. New Media & Society, 20(3), 973–989.

4. Andreoni, M., Miggliozzi, B., Robles, P., & Lu, D. (2022, August 2). The illegal airstrips bringing toxic mining to Brazil’s indigenous land. The New York Times. https://www.nytimes.com/interactive/2022/08/02/world/americas/brazil-airstrips-illegal-mining.html

5. Arguedas, A., Banjeree, S., Mont’Alverne, C., Toff, B., Fletcher, R., & Nielsen, R. (2023). News for the powerful and privileged. Reuters Institute.

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