Identifying "horse race" stories in election news

Miriam Boon, Larry Birnbaum

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

Abstract

Modern election news reporting tends to focus on who is winning and on campaign strategies - what is often called "Horse Race" coverage. With the ultimate goals of better understanding the mix of election story types presented by different venues, helping people to understand their own news consumption, and recommending stories with more useful content, we explore methods for automatic classification of election news stories. We also describe a plugin that recognizes "Horse Race" articles, and recommends a similar article without the frame.

Original languageEnglish (US)
Title of host publicationProceedings of the 24th International Conference on Intelligent User Interfaces, IUI 2019
PublisherAssociation for Computing Machinery
Pages117-118
Number of pages2
ISBN (Electronic)9781450366731
DOIs
StatePublished - Mar 16 2019
Event24th International Conference on Intelligent User Interfaces, IUI 2019 - Marina del Ray, United States
Duration: Mar 16 2019Mar 20 2019

Publication series

NameInternational Conference on Intelligent User Interfaces, Proceedings IUI

Conference

Conference24th International Conference on Intelligent User Interfaces, IUI 2019
CountryUnited States
CityMarina del Ray
Period3/16/193/20/19

Keywords

  • Computational journalism
  • Natural language processing

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction

Cite this

Boon, M., & Birnbaum, L. (2019). Identifying "horse race" stories in election news. In Proceedings of the 24th International Conference on Intelligent User Interfaces, IUI 2019 (pp. 117-118). (International Conference on Intelligent User Interfaces, Proceedings IUI). Association for Computing Machinery. https://doi.org/10.1145/3308557.3308707