Repository landing page

We are not able to resolve this OAI Identifier to the repository landing page. If you are the repository manager for this record, please head to the Dashboard and adjust the settings.

Abstract

Today’s digital society creates an environment potentially conducive to the exchange of deceptive information. The dissemination of misleading information can have severe consequences on society. This research investigates the possibility of using shared characteristics among reviews, news articles, and emails to detect deception in text-based communication using machine learning techniques. The experiment discussed in this paper examines the use of Bag of Words and Part of Speech tag features to detect deception on the aforementioned types of communication using Neural Networks, Support Vector Machine, Naïve Bayesian, Random Forest, Logistic Regression, and Decision Tree. The contribution of this paper is two-fold. First, it provides initial insight into the identification of text communication cues useful in detecting deception across different types of text-based communication. Second, it provides a foundation for future research involving the application of machine learning algorithms to detect deception on different types of text communication

Similar works

Full text

thumbnail-image

ScholarSpace at University of Hawai'i at Manoa

redirect
Last time updated on 22/01/2021

Having an issue?

Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.