A Survey on Event-based News Narrative Extraction
- URL: http://arxiv.org/abs/2302.08351v1
- Date: Thu, 16 Feb 2023 15:11:53 GMT
- Title: A Survey on Event-based News Narrative Extraction
- Authors: Brian Keith Norambuena, Tanushree Mitra, Chris North
- Abstract summary: This survey presents an extensive study of research in the area of event-based news narrative extraction.
We screened over 900 articles that yielded 54 relevant articles.
Based on the reviewed studies, we identify recent trends, open challenges, and potential research lines.
- Score: 10.193264105560862
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Narratives are fundamental to our understanding of the world, providing us
with a natural structure for knowledge representation over time. Computational
narrative extraction is a subfield of artificial intelligence that makes heavy
use of information retrieval and natural language processing techniques.
Despite the importance of computational narrative extraction, relatively little
scholarly work exists on synthesizing previous research and strategizing future
research in the area. In particular, this article focuses on extracting news
narratives from an event-centric perspective. Extracting narratives from news
data has multiple applications in understanding the evolving information
landscape. This survey presents an extensive study of research in the area of
event-based news narrative extraction. In particular, we screened over 900
articles that yielded 54 relevant articles. These articles are synthesized and
organized by representation model, extraction criteria, and evaluation
approaches. Based on the reviewed studies, we identify recent trends, open
challenges, and potential research lines.
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