Media Bias by the Numbers: Challenges and Opportunities in the Empirical Study of Partisan News

Groeling, Tim

doi:10.1146/annurev-polisci-040811-115123

Cited by 149 publications

(103 citation statements)

References 49 publications

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“…We acknowledge that sometimes this systematic influence of mass media coverage is complemented by an even more active role when certain media outlets become actors with their own political goals. In countries like the United States, where partisan outlets are on the rise (Groeling, ), and in the United Kingdom, where partisan outlets have been a constant feature of the media system (Deacon & Wring, ), the media's influence may go beyond the double function we conceptualized here. Yet, we believe that, rather than partisan or ideological, the main political role of the media is systemic and structural and thus best studied from the perspective of the political actors who are confronted with it and try to use it to their advantage.…”

Section: Resultsmentioning

confidence: 99%

Information and Arena: The Dual Function of the News Media for Political Elites

Aelst

Walgrave

2016

J Commun

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How do individual politicians use the news media to reach their political goals? This study addresses the question by proposing an actor-centered, functional approach. We distinguish two essential functions (and sub-functions) the mass media have for political elites. The media are a source of information; politicians depend on it for pure information and they can profit from the momentum generated by media information. The media also are an arena elites need access to in order to promote themselves and their issues. These two functions offer certain politicians a structural advantage over others and, hence, are relevant for the power struggle among political elites. A systematic functional account allows to compare the role of the media across politicians and political systems.

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Section: Resultsmentioning

confidence: 99%

Information and Arena: The Dual Function of the News Media for Political Elites

Aelst

Walgrave

2016

J Commun

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“…Media bias and labeling of media on a political axis is a field in itself (media and communication studies), and hence, this is not a big limitation. See the work by Groeling [22] for a review on media bias and ways to label media sources.…”

Section: Discussionmentioning

confidence: 99%

Political Discourse on Social Media

Garimella

Morales

Gionis

et al. 2018

Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18

238

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Echo chambers, i.e., situations where one is exposed only to opinions that agree with their own, are an increasing concern for the political discourse in many democratic countries. This paper studies the phenomenon of political echo chambers on social media. We identify the two components in the phenomenon: the opinion that is shared, and the "chamber" (i.e., the social network) that allows the opinion to "echo" (i.e., be re-shared in the network)and examine closely at how these two components interact. We define a production and consumption measure for social-media users, which captures the political leaning of the content shared and received by them. By comparing the two, we find that Twitter users are, to a large degree, exposed to political opinions that agree with their own. We also find that users who try to bridge the echo chambers, by sharing content with diverse leaning, have to pay a "price of bipartisanship" in terms of their network centrality and content appreciation. In addition, we study the role of "gatekeepers, " users who consume content with diverse leaning but produce partisan content (with a single-sided leaning), in the formation of echo chambers. Finally, we apply these findings to the task of predicting partisans and gatekeepers from social and content features. While partisan users turn out relatively easy to identify, gatekeepers prove to be more challenging.

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“…Groseclosea et al [21] propose a method to estimate the ideology of various media sources by comparing the number of citations to think tanks and policy groups to those of Congress members. For a complete survey of methods on measuring ideology of media and media bias, please refer to Groeling et al [20]. Reducing polarization.…”

Section: Related Workmentioning

confidence: 99%

Joint Non-negative Matrix Factorization for Learning Ideological Leaning on Twitter

Lahoti

Garimella

Gionis

2018

Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining

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People are shifting from traditional news sources to online news at an incredibly fast rate. However, the technology behind online news consumption promotes content that con rms the users' existing point of view. This phenomenon has led to polarization of opinions and intolerance towards opposing views. Thus, a key problem is to model information lter bubbles on social media and design methods to eliminate them. In this paper, we use a machine-learning approach to learn a liberal-conservative ideology space on Twitter, and show how we can use the learned latent space to tackle the lter bubble problem.We model the problem of learning the liberal-conservative ideology space of social media users and media sources as a constrained non-negative matrix-factorization problem. Our model incorporates the social-network structure and content-consumption information in a joint factorization problem with shared latent factors. We validate our model and solution on a real-world Twitter dataset consisting of controversial topics, and show that we are able to separate users by ideology with over 90 % purity. When applied to media sources, our approach estimates ideology scores that are highly correlated (Pearson correlation 0.9) with ground-truth ideology scores. Finally, we demonstrate the utility of our model in real-world scenarios, by illustrating how the learned ideology latent space can be used to develop exploratory and interactive interfaces that can help users in di using their information lter bubble.

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Media Bias by the Numbers: Challenges and Opportunities in the Empirical Study of Partisan News

Cited by 149 publications

References 49 publications

Information and Arena: The Dual Function of the News Media for Political Elites

Information and Arena: The Dual Function of the News Media for Political Elites

Political Discourse on Social Media

Joint Non-negative Matrix Factorization for Learning Ideological Leaning on Twitter

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