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Quotes are critical for establishing credibility in news articles. A directquote enclosed in quotation marks has a strong visual appeal and is a sign of areliable citation. Unfortunately, this journalistic practice is not strictlyfollowed, and a quote in the headline is often "contextomized." Such a quoteuses words out of context in a way that alters the speaker's intention so thatthere is no semantically matching quote in the body text. We present QuoteCSE,a contrastive learning framework that represents the embedding of news quotesbased on domain-driven positive and negative samples to identify such aneditorial strategy. The dataset and code are available athttps://github.com/ssu-humane/contextomized-quote-contrastive.

Detecting Contextomized Quotes in News Headlines by Contrastive Learning