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2023 | OriginalPaper | Chapter

Fake Review Detection with Concept Drift in the Data: A Survey

Authors : Ketan Sanjay Desale, Swati Shinde, Nikita Magar, Snehal Kullolli, Anjali Kurhade

Published in: Proceedings of Seventh International Congress on Information and Communication Technology

Publisher: Springer Nature Singapore

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Abstract

Online reviews have a great impact on the e-commerce industry. Online users are free to post their perspective on products, which might not always be unbiased or accurate. Such unbiased reviews from the customers can affect both buyers and sellers in the industry. The details of this paper focus on a fake review detection system. This paper examines different techniques used in fake review detection which involves data pre-processing to pre-process and extract features from raw data, classification to classify review as fake or real. Also, our study deals with drift in data, its detection methods, as well as drift adaptation strategies.

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Gutierrez-Espinoza L, Abri F, Siami Namin A, Jones KS, Sears DRW (2020) Ensemble learning for detecting fake reviews. In: 2020 IEEE 44th annual computers, software, and applications conference (COMPSAC), pp 1320–1325. https://doi.org/10.1109/COMPSAC48688.2020.00-73

Elmogy A, Tariq U, Mohammed A, Ibrahim A (2021) Fake reviews detection using supervised machine learning. Int J Adv Comput Sci Appl 12(1):601–606

Sihombing A, Fong ACM (2019) Fake review detection on yelp dataset using classification techniques in machine learning. In: 2019 international conference on contemporary computing and informatics (IC3I), pp 64–68. https://doi.org/10.1109/IC3I46837.2019.9055644

Navale G, Kurkute S, Amey R, Kamble K (2020) Detection of fake reviews using machine learning algorithm. Int J Future Gener Commun Netw 13(1):415–419

Ligthart A, Catal C, Tekinerdogan B (2021) Analyzing the effectiveness of semi-supervised learning approaches for opinion spam classification. Appl Soft Comput 101. https://doi.org/10.1016/j.asoc.2020.107023. https://www.sciencedirect.com/science/article/pii/S1568494620309625

Viji D, Asawa N, Burreja T (2020) Fake reviews of customer detection using machine learning models. Int J Adv Sci Technol 29(6):86–94. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/11297

Wang J, Kan H, Meng F, Mu Q, Shi G, Xiao X (2020) Fake review detection based on multiple feature fusion and rolling collaborative training. IEEE Access 8:182625–182639. https://doi.org/10.1109/access.2020.3028588CrossRef

Le H, Kim B (2020) Detection of fake reviews on social media using machine learning algorithms. Issues Inf Syst 21(1):185–194. https://doi.org/10.48009/1is202185-194

Gözüaçk Ö, Büyükçakır A, Bonab H, Can F (2019) Unsupervised concept drift detection with a discriminative classifier. In: Proceedings of the 28th ACM international conference on information and knowledge management (CIKM ’19). Association for computing machinery, New York, NY, USA, 2365-2368. https://doi.org/10.1145/3357384.3358144

10.

Priya S, Uthra RA (2021) Deep learning framework for handling concept drift and class imbalanced complex decision-making on streaming data. Complex Intell Syst. https://doi.org/10.1007/s40747-021-00456-0CrossRef

11.

Desale KS, Shinde SV (2022) Addressing concept drifts using deep learning for heart disease prediction: a review. In: Gupta D, Khanna A, Kansal V, Fortino G, Hassanien AE (eds) Proceedings of second doctoral symposium on computational intelligence. Advances in intelligent systems and computing, vol 1374. Springer, Singapore. https://doi.org/10.1007/978-981-16-3346-113

12.

Shahariar GM, Biswas S, Omar F, Shah FM, Binte Hassan S (2019) Spam review detection using deep learning. In: 2019 IEEE 10th annual information technology, electronics and mobile communication conference (IEMCON), pp 0027–0033. https://doi.org/10.1109/IEMCON.2019.8936148

13.

Mohawesh R, Tran S, Ollington R, Xu S (2021) Analysis of concept drift in fake reviews detection. Expert Syst Appl 169. https://doi.org/10.1016/j.eswa.2020.114318. https://www.sciencedirect.com/science/article/pii/S0957417420310137

Title: Fake Review Detection with Concept Drift in the Data: A Survey
Authors: Ketan Sanjay Desale
Swati Shinde
Nikita Magar
Snehal Kullolli
Anjali Kurhade
Publisher: Springer Nature Singapore
Book: Proceedings of Seventh International Congress on Information and Communication Technology
Print ISBN: 978-981-19-1609-0

Electronic ISBN: 978-981-19-1610-6

Copyright Year: 2023
DOI: https://doi.org/10.1007/978-981-19-1610-6_63

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