Paper Info
Title
Who is the Hero, the Villain, and the Victim?: Detection of Roles in News Articles using Natural Language Techniques.
Abstract
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, well-known 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 well-understood event sequences in a more prosaic manner, e.g., for information extraction.
Year
DOI
Venue
2018
10.1145/3172944.3172993
IUI
Keywords
Field
DocType
Computational journalism, entity recognition, information extraction, role detection, contextual information, sentiment analysis
Media literacy,Computational journalism,HERO,Sentiment analysis,Computer science,Narrative,Archetype,Human–computer interaction,Natural language,Information extraction,Linguistics
Conference
ISBN
Citations 
PageRank 
978-1-4503-4945-1
0
0.34
References 
Authors
4
3
Name
Order
Citations
PageRank
Diego Gomez-Zara103.04
Miriam L. Boon210.75
Lawrence A. Birnbaum372.60