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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.
|Title of host publication||Data Science for Fake News: Surveys and Perspectives|
|Editors||Deepak Padmanabhan, Tanmoy Chakraborty, Cheng Long, Santhosh Kumar G|
|Publication status||Published - 30 Apr 2021|
|Name||The Information Retrieval Series|
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