The Detection Of Spam in Various OM Through Ontological Method

Many individuals use the opinions posted on social media these days when deciding what goods or services to purchase. Opinion spam identification is a challenging task because individuals and organizations can both create bogus evaluations for various reasons. They create fictitious reviews to decei...

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Bibliographic Details
Published in:	2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) pp. 1241 - 1245
Main Authors:	Chaudhary, Diwakar, Alzubaidi, Laith H., Attiwi, Madi Hashem, Manwal, Manika, Abdulsada, Zainab. R., Alwan, Ali Saad, Mudhafar, Mustafa
Format:	Conference Proceeding
Language:	English
Published:	IEEE 14-05-2024
Subjects:	Accuracy Automation E-Commercial Fake Review Knowledge based systems Ontologies Ontology Opinion Spam Organizations Reviews Social networking (online)
Online Access:	Get full text
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Summary:	Many individuals use the opinions posted on social media these days when deciding what goods or services to purchase. Opinion spam identification is a challenging task because individuals and organizations can both create bogus evaluations for various reasons. They create fictitious reviews to deceive readers or use automation to trigger the detection system by elevating or lowering the status of the target products to harm their reputations or boost them. In this work, we offer a novel method to detect opinion spam with good accuracy by leveraging knowledge-based Ontology.
DOI:	10.1109/ICACITE60783.2024.10616716