Sentence Embeddings and Semantic Entity Extraction for Identification of Topics of Short Fact-Checked Claims

Sentence Embeddings and Semantic Entity Extraction for Identification of Topics of Short Fact-Checked Claims

The objective of this research was to design a method to assign topics to claims debunked by fact-checking agencies. During the fact-checking process, access to more structured knowledge is necessary; therefore, we aim to describe topics with semantic vocabulary. Classification of topics should go b...

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Bibliographic Details
Main Authors: Krzysztof Węcel, Marcin Sawiński, Włodzimierz Lewoniewski, Milena Stróżyna, Ewelina Księżniak, Witold Abramowicz
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Information
Subjects:
sentence embeddings
semantic indexing
DBpedia
topic modeling
fake news
narratives
Online Access:https://www.mdpi.com/2078-2489/15/10/659
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https://www.mdpi.com/2078-2489/15/10/659

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