Who is the hero, the villain, and the victim? Detection of roles in news articles using natural language techniques

Diego Gomez-Zara, Miriam Boon, Lawrence A Birnbaum

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


News articles often use narrative frames to present people, organizations, and facts. These narrative frames follow cultural archetypes, enabling readers to associate each of the presented elements with familiar stereotypes, wellknown characters, and recognizable outcomes. In this way, authors can cast real people or organizations as heroes, villains, or victims. We present a system that identifies the main entities of a news article, and determines which is being cast as a hero, a villain, or a victim. As currently implemented, this system interacts directly with news consumers through a browser extension. Our hope is that by informing readers when an entity is cast in one of these roles, we can make implicit bias explicit, and thereby assist readers in applying their media literacy skills. This approach can also be used to identify roles in wellunderstood event sequences in a more prosaic manner, e.g., for information extraction.

Original languageEnglish (US)
Title of host publicationIUI 2018 - Proceedings of the 23rd International Conference on Intelligent User Interfaces
PublisherAssociation for Computing Machinery
Number of pages5
ISBN (Electronic)9781450349451
StatePublished - Mar 5 2018
Event23rd ACM International Conference on Intelligent User Interfaces, IUI 2018 - Tokyo, Japan
Duration: Mar 7 2018Mar 11 2018

Publication series

NameInternational Conference on Intelligent User Interfaces, Proceedings IUI


Other23rd ACM International Conference on Intelligent User Interfaces, IUI 2018


  • Computational journalism
  • Contextual information
  • Entity recognition
  • Information extraction
  • Role detection
  • Sentiment analysis

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction

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