Detecting News Bias with Sentence Salience and Hierarchical Structures

Detecting News Bias with Sentence Salience and Hierarchical Structures | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 20 February 2025 V1 Latest version Share on Detecting News Bias with Sentence Salience and Hierarchical Structures Authors : 金城 易 , ShaoHua Jiang 0009-0003-9548-2152 [email protected] , and QiPeng Wen Authors Info & Affiliations https://doi.org/10.22541/au.174004415.53467505/v1 240 views 140 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract News communication is not only a process of information transmission, but also a means of expressing and shaping ideologies. Journalists often embed different political biases in news reports on the same event, depending on their perspectives. Therefore, detecting political bias in news has become a key tool for understanding media bias and uncovering hidden communication strategies. It helps identify politically biased news at its source, thereby reducing the media's influence on public perception. This paper proposes a tree-structured hierarchical model for detecting political bias in news, where elements such as titles, bodies, and sentences serve as nodes. A new method is introduced to extract the central sentence of the news, forming a primary-secondary relationship between sentences. Experimental results show that our model is highly effective in detecting political bias in news. Supplementary Material File (wileynjdv5_ama (1).pdf) Download 1.01 MB Information & Authors Information Version history V1 Version 1 20 February 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords media bias detection multi-perspective political bias of news tree structure Authors Affiliations 金城 易 Hunan Normal University View all articles by this author ShaoHua Jiang 0009-0003-9548-2152 [email protected] Hunan Normal University View all articles by this author QiPeng Wen Hunan Normal University View all articles by this author Metrics & Citations Metrics Article Usage 240 views 140 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation 金城 易, ShaoHua Jiang, QiPeng Wen. Detecting News Bias with Sentence Salience and Hierarchical Structures. Authorea . 20 February 2025. DOI: https://doi.org/10.22541/au.174004415.53467505/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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