Multi-CoPED: A multilingual multi-Task approach for coding political event data on conflict and mediation domain

Erick Skorupa Parolin, Mohammadsaleh Hosseini, Yibo Hu, Latifur Khan, Patrick T. Brandt, Javier Osorio, Vito D'Orazio

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

5 Scopus citations

Abstract

Political and social scientists monitor, analyze and predict political unrest and violence, preventing (or mitigating) harm, and promoting the management of global conflict. They do so using event coder systems, which extract structured representations from news articles to design forecast models and event-driven continuous monitoring systems. Existing methods rely on expensive manual annotated dictionaries and do not support multilingual settings. To advance the global conflict management, we propose a novel model, Multi-CoPED (Multilingual Multi-Task Learning BERT for Coding Political Event Data), by exploiting multi-Task learning and state-of-The-Art language models for coding multilingual political events. This eliminates the need for expensive dictionaries by leveraging BERT models' contextual knowledge through transfer learning. The multilingual experiments demonstrate the superiority of Multi-CoPED over existing event coders, improving the absolute macro-Averaged F1-scores by 23.3% and 30.7% for coding events in English and Spanish corpus, respectively. We believe that such expressive performance improvements can help to reduce harms to people at risk of violence.

Original languageEnglish (US)
Title of host publicationAIES 2022 - Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society
PublisherAssociation for Computing Machinery, Inc
Pages700-711
Number of pages12
ISBN (Electronic)9781450392471
DOIs
StatePublished - Jul 26 2022
Event5th AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society, AIES 2022 - Oxford, United Kingdom
Duration: Aug 1 2022Aug 3 2022

Publication series

NameAIES 2022 - Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society

Conference

Conference5th AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society, AIES 2022
Country/TerritoryUnited Kingdom
CityOxford
Period8/1/228/3/22

Keywords

  • artificial intelligence and geopolitics
  • event coding
  • natural language processing
  • political conflict
  • social conflict
  • transfer learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Social Sciences (miscellaneous)

Fingerprint

Dive into the research topics of 'Multi-CoPED: A multilingual multi-Task approach for coding political event data on conflict and mediation domain'. Together they form a unique fingerprint.

Cite this