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Main Authors: Koushik, Raghavendra, Zenil, Hector
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2510.21838
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author Koushik, Raghavendra
Zenil, Hector
author_facet Koushik, Raghavendra
Zenil, Hector
contents While traditionally not considered part of the scientific method, science communication is increasingly playing a pivotal role in shaping scientific practice. Researchers are now frequently compelled to publicise their findings in response to institutional impact metrics and competitive grant environments. This shift underscores the growing influence of media narratives on both scientific priorities and public perception. In a current trend of personality-driven reporting, we examine patterns in science communication that may indicate biases of different types, towards topics and researchers. We focused and applied our methodology to a corpus of media coverage from three of the most prominent scientific media outlets: Wired, Quanta, and The New Scientist -- spanning the past 5 to 10 years. By mapping linguistic patterns, citation flows, and topical convergence, our objective was to quantify the dimensions and degree of bias that influence the credibility of scientific journalism. In doing so, we seek to illuminate the systemic features that shape science communication today and to interrogate their broader implications for epistemic integrity and public accountability in science. We present our results with anonymised journalist names but conclude that personality-driven media coverage distorts science and the practice of science flattening rather than expanding scientific coverage perception. Keywords : selective sourcing, bias, scientific journalism, Quanta, Wired, New Scientist, fairness, balance, neutrality, standard practices, distortion, personal promotion, communication, media outlets.
format Preprint
id arxiv_https___arxiv_org_abs_2510_21838
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Quantitative Approach to Estimating Bias, Favouritism and Distortion in Scientific Journalism
Koushik, Raghavendra
Zenil, Hector
Digital Libraries
While traditionally not considered part of the scientific method, science communication is increasingly playing a pivotal role in shaping scientific practice. Researchers are now frequently compelled to publicise their findings in response to institutional impact metrics and competitive grant environments. This shift underscores the growing influence of media narratives on both scientific priorities and public perception. In a current trend of personality-driven reporting, we examine patterns in science communication that may indicate biases of different types, towards topics and researchers. We focused and applied our methodology to a corpus of media coverage from three of the most prominent scientific media outlets: Wired, Quanta, and The New Scientist -- spanning the past 5 to 10 years. By mapping linguistic patterns, citation flows, and topical convergence, our objective was to quantify the dimensions and degree of bias that influence the credibility of scientific journalism. In doing so, we seek to illuminate the systemic features that shape science communication today and to interrogate their broader implications for epistemic integrity and public accountability in science. We present our results with anonymised journalist names but conclude that personality-driven media coverage distorts science and the practice of science flattening rather than expanding scientific coverage perception. Keywords : selective sourcing, bias, scientific journalism, Quanta, Wired, New Scientist, fairness, balance, neutrality, standard practices, distortion, personal promotion, communication, media outlets.
title A Quantitative Approach to Estimating Bias, Favouritism and Distortion in Scientific Journalism
topic Digital Libraries
url https://arxiv.org/abs/2510.21838