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2021 | OriginalPaper | Buchkapitel

Fake Review Classification Using Supervised Machine Learning

verfasst von : Hanif Khan, Muhammad Usama Asghar, Muhammad Zubair Asghar, Gautam Srivastava, Praveen Kumar Reddy Maddikunta, Thippa Reddy Gadekallu

Erschienen in: Pattern Recognition. ICPR International Workshops and Challenges

Verlag: Springer International Publishing

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Abstract

The revolution of social media has propelled the online community to take advantage of online reviews for not only posting feedback about the products, services, and other issues but also assists individuals to analyze user’s feedback for making purchase decisions, and companies for improving the quality of manufactured goods. However, the propagation of fake reviews has become an alarming issue, as it deceives online users while purchasing and promotes or demotes the reputation of competing brands. In this work, we propose a supervised learning-based technique for the detection of fake reviews from the online textual content. The study employs machine learning classifiers for bifurcating fake and genuine reviews. Experimental results are evaluated against different evaluation measures and the performance of the proposed system is compared with baseline works.

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Vorheriges Kapitel Skeleton-Based Methods for Speaker Action Classification on Lecture Videos
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Metadaten
Titel
Fake Review Classification Using Supervised Machine Learning
verfasst von
Hanif Khan
Muhammad Usama Asghar
Muhammad Zubair Asghar
Gautam Srivastava
Praveen Kumar Reddy Maddikunta
Thippa Reddy Gadekallu
Copyright-Jahr
2021
Buch
Pattern Recognition. ICPR International Workshops and Challenges

Print ISBN: 978-3-030-68798-4

Electronic ISBN: 978-3-030-68799-1

Copyright-Jahr: 2021

DOI
https://doi.org/10.1007/978-3-030-68799-1_19

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