A New Approach for Deception Detection in Open Domain Text

A New Approach for Deception Detection in Open Domain Text

Jamil R. Alzghoul, Muath Alzghool, Emad E. Abdallah
Copyright: © 2021 |Pages: 13
DOI: 10.4018/IJBAN.2021070101
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Abstract

The gigantic growth of platforms that give individuals the ability to write a review that is visible to everyone and the huge number of documents shared on the internet have triggered the researchers to try to detect if these platforms are trying to mislead and deceive people. There is a crucial need to find ways to automatically identify fake reviews and detect deceptive people or groups. The main aim of this research is to detect deception in open domain text by using a machine learning technique. Several sets of features are used to analyse the text including unigram, part of speech, and production rules. The experimental results showed that combined feature sets of (part of speech and production rules) using the support vector machine classifier achieve the best accuracy, and it clearly improves on the accuracy of the results reported in a previous study.
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Literature Review

Several studies have been conducted to identify deceptive content in many domains; however, very little work has been carried out on the automatic detection of deceptive language in written texts, especially in the open text domain.

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