No permanent friends or enemies: Tracking relationships between nations from news

Xiaochuang Han, Eunsol Choi, Chenhao Tan

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

Abstract

Understanding the dynamics of international politics is important yet challenging for civilians. In this work, we explore unsupervised neural models to infer relations between nations from news articles. We extend existing models by incorporating shallow linguistics information and propose a new automatic evaluation metric that aligns relationship dynamics with manually annotated key events. As understanding international relations requires carefully analyzing complex relationships, we conduct in-person human evaluations with three groups of participants. Overall, humans prefer the outputs of our model and give insightful feedback that suggests future directions for human-centered models. Furthermore, our model reveals interesting regional differences in news coverage. For instance, with respect to US-China relations, Singaporean media focus more on “strengthening” and “purchasing”, while US media focus more on “criticizing” and “denouncing”.

Original languageEnglish (US)
Title of host publicationLong and Short Papers
PublisherAssociation for Computational Linguistics (ACL)
Pages1660-1676
Number of pages17
ISBN (Electronic)9781950737130
StatePublished - 2019
Event2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019 - Minneapolis, United States
Duration: Jun 2 2019Jun 7 2019

Publication series

NameNAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference
Volume1

Conference

Conference2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019
Country/TerritoryUnited States
CityMinneapolis
Period6/2/196/7/19

ASJC Scopus subject areas

  • Language and Linguistics
  • Computer Science Applications
  • Linguistics and Language

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