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The Table of Media Bias Elements: A sentence-level taxonomy of media bias types and propaganda techniques

Tim Menzner, Jochen L. Leidner

TL;DR

This work introduces a sentence-level taxonomy of media bias and propaganda, comprising 38 bias types across six functional families, presented as the Table of Bias Elements. It addresses the problem that bias arises from concrete linguistic techniques rather than mere outlet positions, validated on 26,464 sentences from newsroom corpora, user submissions, and browsing, with a prevalence survey on a 155-sentence sample and cross-walks to established NLP taxonomies. The methodology is iterative and data-driven, enforcing criteria that each bias type is observable in a single sentence, identifiable without wider context, and elementary in nature. The taxonomy aims to support automated bias detection and media literacy interventions, bridging interdisciplinary insights from political communication and NLP to enable more universal and nuanced bias analysis. Overall, the work provides a flexible, extensible framework for sentence-level bias classification that reduces ambiguity and supports practical applications in detection, education, and research.

Abstract

Public debates about "left-" or "right-wing" news overlook the fact that bias is usually conveyed by concrete linguistic manoeuvres that transcend any single political spectrum. We therefore shift the focus from where an outlet allegedly stands to how partiality is expressed in individual sentences. Drawing on 26,464 sentences collected from newsroom corpora, user submissions and our own browsing, we iteratively combine close-reading, interdisciplinary theory and pilot annotation to derive a fine-grained, sentence-level taxonomy of media bias and propaganda. The result is a two-tier schema comprising 38 elementary bias types, arranged in six functional families and visualised as a "table of media-bias elements". For each type we supply a definition, real-world examples, cognitive and societal drivers, and guidance for recognition. A quantitative survey of a random 155-sentence sample illustrates prevalence differences, while a cross-walk to the best-known NLP and communication-science taxonomies reveals substantial coverage gains and reduced ambiguity.

The Table of Media Bias Elements: A sentence-level taxonomy of media bias types and propaganda techniques

TL;DR

This work introduces a sentence-level taxonomy of media bias and propaganda, comprising 38 bias types across six functional families, presented as the Table of Bias Elements. It addresses the problem that bias arises from concrete linguistic techniques rather than mere outlet positions, validated on 26,464 sentences from newsroom corpora, user submissions, and browsing, with a prevalence survey on a 155-sentence sample and cross-walks to established NLP taxonomies. The methodology is iterative and data-driven, enforcing criteria that each bias type is observable in a single sentence, identifiable without wider context, and elementary in nature. The taxonomy aims to support automated bias detection and media literacy interventions, bridging interdisciplinary insights from political communication and NLP to enable more universal and nuanced bias analysis. Overall, the work provides a flexible, extensible framework for sentence-level bias classification that reduces ambiguity and supports practical applications in detection, education, and research.

Abstract

Public debates about "left-" or "right-wing" news overlook the fact that bias is usually conveyed by concrete linguistic manoeuvres that transcend any single political spectrum. We therefore shift the focus from where an outlet allegedly stands to how partiality is expressed in individual sentences. Drawing on 26,464 sentences collected from newsroom corpora, user submissions and our own browsing, we iteratively combine close-reading, interdisciplinary theory and pilot annotation to derive a fine-grained, sentence-level taxonomy of media bias and propaganda. The result is a two-tier schema comprising 38 elementary bias types, arranged in six functional families and visualised as a "table of media-bias elements". For each type we supply a definition, real-world examples, cognitive and societal drivers, and guidance for recognition. A quantitative survey of a random 155-sentence sample illustrates prevalence differences, while a cross-walk to the best-known NLP and communication-science taxonomies reveals substantial coverage gains and reduced ambiguity.
Paper Structure (58 sections, 1 figure, 1 table)

This paper contains 58 sections, 1 figure, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. Media Bias and Propaganda
  4. What drives media bias and how prevalent is it?
  5. What are the consequences of exposure to media bias and propaganda?
  6. How can effects of bias and propaganda be mitigated?
  7. Attempts to Systematize
  8. Terminology
  9. Methodology
  10. The Table of Bias Elements
  11. Asserting
  12. Projection Bias
  13. Speculation Bias
  14. Suggestive Questioning Bias
  15. Unsubstantiated Claims Bias
  16. ...and 43 more sections

Figures (1)

  • Figure 1: Our Table Of Bias Elements