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Computer Science > Computation and Language

arXiv:2302.04465 (cs)
[Submitted on 9 Feb 2023]

Title:Detecting Contextomized Quotes in News Headlines by Contrastive Learning

Authors:Seonyeong Song, Hyeonho Song, Kunwoo Park, Jiyoung Han, Meeyoung Cha
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Abstract:Quotes are critical for establishing credibility in news articles. A direct quote enclosed in quotation marks has a strong visual appeal and is a sign of a reliable citation. Unfortunately, this journalistic practice is not strictly followed, and a quote in the headline is often "contextomized." Such a quote uses words out of context in a way that alters the speaker's intention so that there is no semantically matching quote in the body text. We present QuoteCSE, a contrastive learning framework that represents the embedding of news quotes based on domain-driven positive and negative samples to identify such an editorial strategy. The dataset and code are available at this https URL.
Comments: 8 pages, EACL 2023 (Findings)
Subjects: Computation and Language (cs.CL); Computers and Society (cs.CY)
Cite as: arXiv:2302.04465 [cs.CL]
  (or arXiv:2302.04465v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2302.04465

Submission history

From: Kunwoo Park [view email]
[v1] Thu, 9 Feb 2023 07:04:11 UTC (132 KB)
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