Textual Characteristics of News Title and Body to Detect Fake News: A Reproducibility Study

Anu Shrestha, Francesca Spezzano

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

15 Scopus citations

Abstract

Fake news, a deliberately designed news to mislead others, is becoming a big societal threat with its fast dissemination over the Web and social media and its power to shape public opinion. Many researchers have been working to understand the underlying features that help identify these fake news on the Web. Recently, Horne and Adali found, on a small amount of data, that news title stylistic and linguistic features are better than the same type of features extracted from the news body in predicting fake news. In this paper, we present our attempt to reproduce the same results to validate their findings. We show which of their findings can be generalized to larger political and gossip news datasets.

Original languageEnglish
Title of host publicationAdvances in Information Retrieval - 43rd European Conference on IR Research, ECIR 2021, Proceedings
EditorsDjoerd Hiemstra, Marie-Francine Moens, Josiane Mothe, Raffaele Perego, Martin Potthast, Fabrizio Sebastiani
PublisherSpringer Science and Business Media Deutschland GmbH
Pages120-133
Number of pages14
ISBN (Print)9783030722395
DOIs
StatePublished - 2021
Event43rd European Conference on Information Retrieval, ECIR 2021 - Virtual, Online
Duration: 28 Mar 20211 Apr 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12657 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference43rd European Conference on Information Retrieval, ECIR 2021
CityVirtual, Online
Period28/03/211/04/21

Keywords

  • Fake news
  • Linguistic analysis
  • Misinformation detection on the web

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