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There is no liberal media bias in which news stories political journalists choose to cover.

ABSTRACT: Is the media biased against conservatives? Although a dominant majority of journalists identify as liberals/Democrats and many Americans and public officials frequently decry supposedly high and increasing levels of media bias, little compelling evidence exists as to (i) the ideological or partisan leanings of the many journalists who fail to answer surveys and/or identify as independents and (ii) whether journalists' political leanings bleed into the choice of which stories to cover that Americans ultimately consume. Using a unique combination of a large-scale survey of political journalists, data from journalists' Twitter networks, election returns, a large-scale correspondence experiment, and a conjoint survey experiment, we show definitively that the media exhibits no bias against conservatives (or liberals for that matter) in what news that they choose to cover. This shows that journalists' individual ideological leanings have unexpectedly little effect on the vitally important, but, up to this point, unexplored, early stage of political news generation.

SUBMITTER: Hassell HJG

PROVIDER: S-EPMC7112764 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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There is no liberal media bias in which news stories political journalists choose to cover.

Hassell Hans J G HJG Holbein John B JB Miles Matthew R MR

Science advances 20200401 14

Is the media biased against conservatives? Although a dominant majority of journalists identify as liberals/Democrats and many Americans and public officials frequently decry supposedly high and increasing levels of media bias, little compelling evidence exists as to (i) the ideological or partisan leanings of the many journalists who fail to answer surveys and/or identify as independents and (ii) whether journalists' political leanings bleed into the choice of which stories to cover that Americ ...[more]

PMID: 32270038

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Project description:Previous research on news perception has been dominated by a cognitively oriented perspective on reception processes, whereas emotions have been widely neglected. Consequently, it has remained open which features of a news story might elicit affective responses and hence modulate news perception, shifting the focus to the emotional potential of the narrative. According to the affective-disposition theory, the experience of suspense is the striving force of immersion in fictional dramas. Thereby, a positive affective disposition toward the protagonist of a story and a high likelihood of a bad ending should increase suspense that, in turn, should positively influence reading appreciation and lingering interest in the story. We investigated whether suspense and its determinants also play such a key role in the context of news stories. Study 1 (n = 263) successfully replicated results of an earlier study, whereas Studies 2 (n = 255) and 3 (n = 599) challenged the generalizability of some effects related to manipulated characteristics of a news story. In contrast, correlational relationships between perceived news characteristics and news evaluation were relatively stable. In particular, participants' liking of the protagonist and the perceived likelihood of a good ending were positively associated with suspense, reading appreciation, and lingering interest. This result indicates a preference for happy endings and contradicts the notion that likely negative outcomes are beneficial for suspense and the enjoyment of news stories, as postulated by the affective-disposition theory in the context of fictional dramas. Moreover, experienced suspense reliably mediated the correlations between, on the one hand, participants' liking of the protagonist and the perceived likelihood of a good ending and, on the other hand, reading appreciation and lingering interest. The news story's personal relevance was less influential than expected. Further, we observed a large absence of interaction effects, indicating that central characteristics of a news story can be independently varied to a large degree. In a nutshell, we may conclude that suspense significantly mediates the correlation between perceived news characteristics and the enjoyment of news stories, whereas manipulations of news characteristics do not necessarily influence the enjoyment of narratives as desired.

Project description:Background: Despite a 2010 Kenyan constitutional amendment limiting members of elected public bodies to < two-thirds of the same gender, only 22 percent of the 12th Parliament members inaugurated in 2017 were women. Investigating gender bias in the media is a useful tool for understanding socio-cultural barriers to implementing legislation for gender equality. Natural language processing (NLP) methods, such as word embedding and sentiment analysis, can efficiently quantify media biases at a scope previously unavailable in the social sciences. Methods: We trained GloVe and word2vec word embeddings on text from 1998 to 2019 from Kenya's Daily Nation newspaper. We measured gender bias in these embeddings and used sentiment analysis to predict quantitative sentiment scores for sentences surrounding female leader names compared to male leader names. Results: Bias in leadership words for men and women measured from Daily Nation word embeddings corresponded to temporal trends in men and women's participation in political leadership (i.e., parliamentary seats) using GloVe (correlation 0.8936, p = 0.0067, r 2 = 0.799) and word2vec (correlation 0.844, p = 0.0169, r 2 = 0.712) algorithms. Women continue to be associated with domestic terms while men continue to be associated with influence terms, for both regular gender words and female and male political leaders' names. Male words (e.g., he, him, man) were mentioned 1.84 million more times than female words from 1998 to 2019. Sentiment analysis showed an increase in relative negative sentiment associated with female leaders (p = 0.0152) and an increase in positive sentiment associated with male leaders over time (p = 0.0216). Conclusion: Natural language processing is a powerful method for gaining insights into and quantifying trends in gender biases and sentiment in news media. We found evidence of improvement in gender equality but also a backlash from increased female representation in high-level governmental leadership.

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There is no liberal media bias in which news stories political journalists choose to cover.

Publications

There is no liberal media bias in which news stories political journalists choose to cover.

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