Opinion Spam Detection and Analysis by Identifying Domain Features in Product Reviews

5 Pages Posted: 12 Jun 2019

See all articles by Lakshmi Holla

Lakshmi Holla

Global Academy of Technology, Bangalore

Kavitha K.S.

Global Academy of Technology, Bangalore

Date Written: March 14, 2019

Abstract

With the rapid advent of technology there is an exponential number of users who purchase online products and express their opinions in form of reviews. It is observed that recommending the deserving products to people often depend on the sentiment expressed in the reviews. Classification of the reviews as genuine and fake is one of the hardest problems in the current world. Feature Engineering is an active area of research in text analytics and opinion mining and plays a significant role in extracting features from reviews. Genuine reviews often contain higher percentage of concrete information or domain specific information as these reviews are written based on experience, but spam reviews often lack this information This paper focuses on, using Latent Dirichlet Allocation topic model to extract domain features in product reviews and use this as one of the main features to identify fake reviews.

Keywords: Sentiment Analysis, Latent Dirichlet Allocation, Opinion Mining, Feature Engineering, Text Mining

Suggested Citation

Holla, Lakshmi and K.S., Kavitha, Opinion Spam Detection and Analysis by Identifying Domain Features in Product Reviews (March 14, 2019). Proceedings of International Conference on Sustainable Computing in Science, Technology and Management (SUSCOM), Amity University Rajasthan, Jaipur - India, February 26-28, 2019, Available at SSRN: https://ssrn.com/abstract=3352429 or http://dx.doi.org/10.2139/ssrn.3352429

Lakshmi Holla (Contact Author)

Global Academy of Technology, Bangalore ( email )

Bangalore, 560098
India

Kavitha K.S.

Global Academy of Technology, Bangalore ( email )

Bangalore, 560098
India

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