Linguistic approaches to fake news detection

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

To date, there is no comprehensive linguistic description of fake news. This chapter surveys a range of fake news detection research, focusing specifical-ly on that which adopts a linguistic approach in whole or as part of an inte-grated approach. Areas where linguistics can support fake news characteri-zation and detection are identified; namely, in the adoption of more sys-tematic data selection procedures as found in corpus linguistics, in the recognition of fake news as a probabilistic outcome in classification tech-niques, and in the proposal for integrating linguistics in hybrid approaches to fake news detection. Drawing on the research of linguist Douglas Biber, it is suggested that fake news detection might operate along dimensions of extracted linguistic features.
Original languageEnglish
Title of host publicationData Science for Fake News: Surveys and Perspectives
EditorsDeepak Padmanabhan, Tanmoy Chakraborty, Cheng Long, Santhosh Kumar G
PublisherSpringer
ISBN (Electronic)978-3-030-62696-9
ISBN (Print)978-3030626952
Publication statusPublished - 30 Apr 2021

Publication series

NameThe Information Retrieval Series

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