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From Claim to Evidence: Verifying Chinese Health Claims with Medical Literature

  • Nankai University
  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Ensuring the accuracy of health claims in media is vital for public well-being, and evidence-based claim verification is critical in achieving this goal. However, identifying relevant biomedical literature as evidence for health claims is particularly challenging, especially within cross-genre and cross-lingual contexts. We propose an ad hoc information retrieval (IR) task to identify support for Chinese health claims obtained from Chinese news sources. We demonstrate the feasibility of such a task by presenting experiments on a novel dataset of pairs of Chinese health claims and English biomedical literature. We describe a two-step methodology comprising (i) a selection of the most relevant candidates from 764K research papers, and (ii) a final re-ranking of this selection. Our comprehensive experimental research demonstrates that incorporating domain-specific information significantly enhances retrieval accuracy and claim verification efficacy. This strategy is a major step toward improving the credibility of public health information dissemination and reducing the prevalence of falsehoods in health journalism.

Original languageEnglish
Title of host publicationNatural Language Processing and Chinese Computing - 13th National CCF Conference, NLPCC 2024, Proceedings
EditorsDerek F. Wong, Zhongyu Wei, Muyun Yang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages171-183
Number of pages13
ISBN (Print)9789819794393
DOIs
StatePublished - 2025
Event13th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2024 - Hangzhou, China
Duration: Nov 1 2024Nov 3 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15362 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2024
Country/TerritoryChina
CityHangzhou
Period11/1/2411/3/24

Keywords

  • Chinese health claim
  • Dataset
  • Information retrieval

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