Effects of Partisan Personalization in a News Portal Experiment

Bryanov, Kirill; Watson, Brian; Pingree, Raymond J.; Santia, Martina

doi:10.1093/poq/nfaa011

Cited by 15 publications

(6 citation statements)

References 32 publications

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“…At the same time, Hameleers and van der Meer (2020) found evidence of motivated reasoning in their participants’ evaluation of partisan news media even in instances where individuals forcibly exposed to counter-attitudinal information presented as a credible fact-checking source. Algorithms and news recommendations have also been found to reinforce the incentive for news consumers to consume news they already agree with, and as a result consume fewer reputable mainstream sources of information (Bryanov et al, 2020). However, Peterson and Kagalwala (2021) suggest that part of the polarization reinforced by this kind of high-choice media environment is rooted in partisan individuals’ lack of exposure to counter-attitudinal information, and that exposure to this kind of information that subverts their biases against it can effectively reduce pre-existing hostilities they associate with it.…”

Section: Literature Reviewmentioning

confidence: 99%

Partisan selective exposure and politically polarized attitudes toward disruptive protest

Lorenzano¹,

Moon

Borah

2023

Communication and the Public

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While many Americans support the right to protest, increased animus has recently been directed at protesters themselves, often along partisan ideological lines and in partisan media content. However, there is a lack of research on attitudes toward treatment of protesters in the context of political violence and selective exposure to likeminded partisan sources of information. This study finds that a significant, positive relationship exists between self-identified Republicans and thinking that disruptive protesters deserve to be “roughed up,” while identifying as a Democrat produced a negative relationship in the same circumstance. Likewise, consumption of conservative partisan media was found to have a positive relationship with the idea of “roughing up” disruptive protesters, while liberal partisan media was found to have a negative relationship. However, selective exposure to attitude-affirming media only had a significant impact among self-identified Democrats, in the sense that Democrats’ selective exposure to left-leaning media was associated with less support for “roughing up” disruptive protesters.

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Section: Literature Reviewmentioning

confidence: 99%

Partisan selective exposure and politically polarized attitudes toward disruptive protest

Lorenzano¹,

Moon

Borah

2023

Communication and the Public

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“…While the existence of algorithmically generated filter bubbles and echo chambers remains debated (Zuiderveen Borgesius et al, 2016; Dubois and Blank, 2018; Bodó et al, 2019; Bruns, 2019), the negative consequences of selective exposure nevertheless exist in subtle and complicated ways. For example, in a test setting, users exposed to partisan news determined it to be more reliable than “mainstream” news, the consumption of which was concomitantly reduced (Bryanov et al, 2020; cf. Möller et al, 2018).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Personalisation in Journalism: Ethical insights and blindspots in Finnish legacy media

et al. 2022

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The algorithmic personalisation and recommendation of media content has resulted in considerable discussion on related ethical, epistemic and societal concerns. While technologies of personalisation are widely employed by social media platforms, they are currently also being instituted in journalistic media. The objective of this study is to explore how concerns about algorithms are articulated and addressed when technologies of personalisation meet with long-standing journalistic values, norms and publicist missions. It first distinguishes five normative concerns related to personalisation: autonomy, opacity, privacy, selective exposure and discrimination. It then traces the ways that these issues are navigated in the context of journalistic media in Finland where the implications of algorithmic media technologies have received considerable attention. The results indicate that personalisation challenges traditional notions of journalism, including those of choosing what is important and relevant and providing the same content to everyone. However, aspects of personalisation also have a long history within journalistic practices, and new technologies of personalisation are being adapted to accord with journalistic norms and aims. Based on these results, ethical blindspots concerning privacy and discrimination are also identified.

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“…To maximise the likelihood of engagement with diverse news, methods taking into account individual latitudes of diversity should determine which content is acceptable for a given reader at a given point in time. Thereby, situations where introducing too much diversity limits user satisfaction (Bryanov et al, 2020) could be prevented.…”

Section: Individual-level Differencesmentioning

confidence: 99%

Are we human, or are we users? The role of natural language processing in human-centric news recommenders that nudge users to diverse content

Reuver¹,

Mattis²,

Sax

et al. 2021

Proceedings of the 1st Workshop on NLP for Positive Impact

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In this position paper, we present a research agenda and ideas for facilitating exposure to diverse viewpoints in news recommendation. Recommending news from diverse viewpoints is important to prevent potential filter bubble effects in news consumption, and stimulate a healthy democratic debate. To account for the complexity that is inherent to humans as citizens in a democracy, we anticipate (among others) individual-level differences in acceptance of diversity. We connect this idea to techniques in Natural Language Processing, where distributional language models would allow us to place different users and news articles in a multidimensional space based on semantic content, where diversity is operationalized as distance and variance. In this way, we can model individual "latitudes of diversity" for different users, and thus personalize viewpoint diversity in support of a healthy public debate. In addition, we identify technical, ethical and conceptual issues related to our presented ideas. Our investigation describes how NLP can play a central role in diversifying news recommendations.

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Effects of Partisan Personalization in a News Portal Experiment

Cited by 15 publications

References 32 publications

Partisan selective exposure and politically polarized attitudes toward disruptive protest

Partisan selective exposure and politically polarized attitudes toward disruptive protest

Personalisation in Journalism: Ethical insights and blindspots in Finnish legacy media

Are we human, or are we users? The role of natural language processing in human-centric news recommenders that nudge users to diverse content

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