CLDLOct 9, 2018

Fake Comment Detection Based on Sentiment Analysis

arXiv:1811.05825v14 citations
Originality Synthesis-oriented
AI Analysis

This addresses the issue of fake comments for users relying on online reviews, but it appears incremental as it applies an existing method to a known problem.

The paper tackled the problem of fake comments in e-commerce and review websites, which mislead users, by using sentiment analysis for detection, but no concrete results or numbers are provided.

With the development of the E-commerce and reviews website, the comment information is influencing people's life. More and more users share their consumption experience and evaluate the quality of commodity by comment. When people make a decision, they will refer these comments. The dependency of the comments make the fake comment appear. The fake comment is that for profit and other bad motivation, business fabricate untrue consumption experience and they preach or slander some products. The fake comment is easy to mislead users' opinion and decision. The accuracy of humans identifying fake comment is low. It's meaningful to detect fake comment using natural language processing technology for people getting true comment information. This paper uses the sentimental analysis to detect fake comment.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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