Social media users (under)appreciate the news: An application of hostile media bias to news disseminated on Facebook

2021 ◽  
pp. 073953292110470
Author(s):  
Sherice Gearhart ◽  
Alexander Moe ◽  
Derrick Holland

News outlets rely on social media to freely distribute content, offering a venue for users to comment on news. This exposes individuals to user comments prior to reading news articles, which can influence perceptions of news content. A 2 × 2 between-subject experiment (N = 690) tested the hostile media bias theory via the influence of comments seen before viewing a news story on perceptions of bias and credibility. Results show that user comments induce hostile media perceptions.

Author(s):  
Arnout B. Boot ◽  
Katinka Dijkstra ◽  
Rolf A. Zwaan

AbstractContemporary news often spreads via social media. This study investigated whether the processing and evaluation of online news content can be influenced by Likes and peer-user comments. An online experiment was designed, using a custom-built website that resembled Facebook, to explore how Likes, positive comments, negative comments, or a combination of positive and negative comments would affect the reader’s processing of news content. The results showed that especially negative comments affected the readers’ personal opinions about the news content, even in combination with other positive comments: They (1) induced more negative attitudes, (2) lowered intent to share it, (3) reduced agreement with conveyed ideas, (4) lowered perceived attitude of the general public, and (5) decreased the credibility of the content. Against expectations, the presence of Likes did not affect the readers, irrespective of the news content. An important consideration is that, while the negative comments were persuasive, they comprised subjective, emotive, and fallacious rhetoric. Finally, negativity bias, the perception of expert authority, and cognitive heuristics are discussed as potential explanations for the persuasive effect of negative comments.


2016 ◽  
Vol 36 (1) ◽  
pp. 21-35 ◽  
Author(s):  
Gi Woong Yun ◽  
Sung-Yeon Park ◽  
Sooyoung Lee ◽  
Mark A. Flynn

An experiment was conducted with college students to examine the effects of source and user comments on the perceptions of a shared news story embedded in a blog post. When the shared news was credited to a news organization source incongruent with the participants’ political orientation, it was perceived to be biased against the participants’ issue position. When credited to a congruent source, the same news was perceived to be biased in favor of the participants’ position. In addition, the shared news from an incongruent source was perceived to have greater influence on others’ issue position than the same news from a congruent source, although perceived reach of the shared news was not different between the two conditions. A subsequent regression analysis identified source and perceived influence, but not perceived reach, as predictors of news bias perception. On the other hand, the second factor, user comments either agreeable or disagreeable to the participants’ issue position, did not influence how the shared news was perceived. In the discussion, theoretical implications of these findings are elaborated, and suggestions are made to refine the methods of shared news research.


2021 ◽  
pp. 146144482110341
Author(s):  
Mikhaila N. Calice ◽  
Luye Bao ◽  
Isabelle Freiling ◽  
Emily Howell ◽  
Michael A. Xenos ◽  
...  

The use of artificial intelligence-based algorithms for the curation of news content by social media platforms like Facebook and Twitter has upended the gatekeeping role long held by traditional news outlets. This has caused some US policymakers to argue that platforms are skewing news diets against them, and such claims are beginning to take hold among some voters. In a nationally representative survey experiment, we explore whether traditional models of media bias perceptions extend to beliefs about algorithmic news bias. We find that partisan cues effectively shape individuals’ attitudes about algorithmic news bias but have asymmetrical effects. Specifically, whereas in-group directional partisan cues stimulate bias perceptions for members of both parties, Democrats, but not Republicans, also respond to out-group cues. We conclude with a discussion about the implications for the formation of attitudes about new technologies and the potential for polarization.


2019 ◽  
Vol 63 (3) ◽  
pp. 374-392 ◽  
Author(s):  
Brian E. Weeks ◽  
Dam Hee Kim ◽  
Lauren B. Hahn ◽  
Trevor H. Diehl ◽  
Nojin Kwak

Target ◽  
2014 ◽  
Vol 26 (3) ◽  
pp. 406-431 ◽  
Author(s):  
Krisztina Károly

This study explores the (re)creation of referential cohesion in Hungarian-English translation and examines the extent to which shifts of reference are motivated by the differences between the languages, the characteristics of the translation type (news translation) and the genre (news story). As referential cohesion is hypothesized to be affected by certain universals of translation, the explicitation and the repetition avoidance hypotheses are also tested. Analyses show considerable shifts of reference in translations, but these are not statistically significant. The corpus also fails to provide evidence for the universals of translation investigated; however, the in-depth analysis of optional shifts suggests that they are conditioned by the discursive features of the genre and contribute to a more explicit presentation of news content.


2019 ◽  
Vol 2019 ◽  
Author(s):  
Edward Hurcombe

This paper empirically investigates how two prominent Australian legacy news outlets – ABC News and News.com.au – operate according to what I term a social media logic of “engagement”, a concept which builds upon van Dijck & Poell’s notion of a social media logic of “popularity”. By a logic of engagement, I mean the necessity to maximize social media attention and interaction metrics. Rather than just valuing “popularity”, platforms instead place value on content that maximizes a multitude of feelings, sentiments, and reactions. Without sufficient engagement, outlets dependent on platforms such as Facebook are threatened by invisibility in the newsfeed. I specifically focus on the operations of ABC News and News.com.au on Facebook from 21 March 2018 – 10 April 2018. Within this period, I collected all the posts from each page, which amounted to 44 posts in total. From these posts, I strategically selected six posts of varying levels of engagement for closer qualitative analysis, with an emphasis on language and imagery. My findings in this paper suggest that the drive for monetizable and algorithmically-valued audience metrics on Facebook can encourage divisive and provocative news content that arouses strong negative feelings and promotes conflict. Trolls are those that deceive other users of their intentions, and seek to sow discord for their own purposes. Thus, it is beneficial to think about a potentially emerging practice of news “trolling”, as it appears that news outlets are adopting faux-naïve, and deliberately incendiary, practices when pursuing engagement.


2019 ◽  
Author(s):  
Robert M Ross ◽  
David Gertler Rand ◽  
Gordon Pennycook

Why is misleading partisan content believed and shared? An influential account posits that political partisanship pervasively biases reasoning, such that engaging in analytic thinking exacerbates motivated reasoning and, in turn, the acceptance of hyperpartisan content. Alternatively, it may be that susceptibility to hyperpartisan misinformation is explained by a lack of reasoning. Across two studies using different subject pools (total N = 1977), we had participants assess true, false, and hyperpartisan headlines taken from social media. We found no evidence that analytic thinking was associated with increased polarization for either judgments about the accuracy of the headlines or willingness to share the news content on social media. Instead, analytic thinking was broadly associated with an increased capacity to discern between true headlines and either false or hyperpartisan headlines. These results suggest that reasoning typically helps people differentiate between low and high quality news content, rather than facilitating political bias.


2021 ◽  
Author(s):  
Rebecca Krauss

In February of 2016, Electric Forest — a four-day electronic music festival from June 23-26 in Rothbury, Michigan —announced a women’s only program called Her Forest. The initiative’s aim was to facilitate feelings of “connection, inspiration, and comfort” (Weiner, 2016) amongst the festival’s female guests. This MRP draws from past research on influence and postfeminism to consider how the Electric Forest brand, as well as its online followers, constructed and discussed Her Forest via Facebook and Instagram. A directed qualitative analysis was applied to 21 of Electric Forest’s Facebook and Instagram posts and 110 associated user comments. The analysis emphasized the powerful impact that social media applications have on the way in which corporate messages are expressed, received, reshaped, supported, and challenged.


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