Aspect-based classification method for review spam detection-Reference-Cited by-同舟云学术

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Aspect-based classification method for review spam detection

Published:2023-08-05 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Cai Mengsi,Du Yonghao,Tan Yuejin,Lu Xin^ORCID

Funder

Natural Science Foundation of Hunan Province

National Natural Science Foundation of China

Social Science Foundation of Hunan Province

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-16293-x.pdf

Reference61 articles.

1. Akoglu L, Chandy R, Faloutsos C (2013). Opinion fraud detection in online reviews by network effects. Seventh Int AAAI Conf Weblogs and Social Media, 7(1), pp.2–11. https://ojs.aaai.org/index.php/ICWSM/article/view/14380. Accessed 2013-07-10

2. Bajaj S, Garg N, Singh S (2017) A novel user-based spam review detection. Procedia Computer Science 122:1009–1015. https://doi.org/10.1016/j.procs.2017.11.467

3. Barbado R, Araque O, Iglesias AC (2019) A framework for fake review detection in online consumer electronics retailers. Inf Process Manage 56(4):1234–1244. https://doi.org/10.1016/j.ipm.2019.03.002

4. Bhuvaneshwari P, Rao AN, Robinson YH (2021) Spam review detection using self attention based CNN and bi-directional LSTM. Multimedia Tools and Applications 80:18107–18124. https://doi.org/10.1007/s11042-021-10602-y

5. Buettner R (2016) Predicting user behavior in electronic markets based on personality-mining in large online social networks: A personality-based product recommender framework. Electron Mark 27:247–265. https://doi.org/10.1007/s12525-016-0228-z

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