Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/28867
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Author(s): Ajao, Oluwaseun
Bhowmik, Deepayan
Zargari, Shahrzad
Title: Sentiment Aware Fake News Detection on Online Social Networks
Citation: Ajao O, Bhowmik D & Zargari S (2019) Sentiment Aware Fake News Detection on Online Social Networks. In: ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE International Conference on Acoustics, Speech, and Signal Processing Proceedings. 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, 12.05.2019-17.05.2019. Piscataway, NJ, USA: IEEE, pp. 2507-2511. https://doi.org/10.1109/ICASSP.2019.8683170
Issue Date: 2019
Date Deposited: 20-Feb-2019
Series/Report no.: IEEE International Conference on Acoustics, Speech, and Signal Processing Proceedings
Conference Name: 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Conference Dates: 2019-05-12 - 2019-05-17
Conference Location: Brighton, UK
Abstract: Messages posted to online social networks (OSN) causes a recent stir due to the intended spread of fake news or rumor. This work aims to understand and analyse the characteristics of fake news especially in relation to sentiments, for the automatic detection of fake news and rumors. Based on empirical observations, we propose a hypothesis that there exists a relation between fake messages or rumours and sentiments of the texts posted online. We verify our hypothesis by comparing with the state-of-the-art baseline text-only fake news detection methods that do not consider sentiments. We performed experiments on standard Twitter fake news dataset and show good improvements in detecting fake news or rumor posts.
Status: AM - Accepted Manuscript
Rights: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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