A Survey on Review Spam Detection Methods using Deep Learning Approach

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Aliarab Mahmoud; FOULADI KAZIM

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Seminar Paper

Paper Information

Seminar: INTERNATIONAL CONFERENCE ON WEB RESEARCH
Year:2022 | Issue:8

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Title

A Survey on Review Spam Detection Methods using Deep Learning Approach

Author(s)

Aliarab Mahmoud | FOULADI KAZIM

Keywords

Review Spam Detection

Opinion Spam

Deep Learning

Convolutional Neural Network

Long Short-Term Memory (LSTM)

Literature Survey

Abstract

Review spam is an opinion written to promote or demote a product or brand on websites and other internet services by some users. Since it is not easy for humans to recognize these types of opinions, a model needs to be provided to detect these types of opinions. In recent years, a lot of research has been done to detect these types of reviews, and with the expansion of deep neural networks and the efficiency of these networks in various issues, in recent years, various types of deep neural networks have been used to identify spam reviews. This paper reviews the proposed Deep Learning methods for the problem of Review Spam Detection. Challenges in this area, evaluation criteria, and datasets in this area are also reviewed.

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APA: Copy

Aliarab, Mahmoud, & FOULADI, KAZIM. (2022). A Survey on Review Spam Detection Methods using Deep Learning Approach. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/949651/en

Vancouver: Copy

Aliarab Mahmoud, FOULADI KAZIM. A Survey on Review Spam Detection Methods using Deep Learning Approach. 2022. Available from: https://sid.ir/paper/949651/en

IEEE: Copy

Mahmoud Aliarab, and KAZIM FOULADI, “A Survey on Review Spam Detection Methods using Deep Learning Approach,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2022, [Online]. Available: https://sid.ir/paper/949651/en

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