Impact of Sentiment Analysis in Fake Online Review Detection
Rakibul Hassan, Md. Rabiul Islam
Abstract
Online business is one of the rapidly growing business sectors of current world. Now-a-days people purchase a lot of things from online shopping sites. Sales of online products are most often review driven. Thus, detecting deceptive reviews is getting more importance day by day. Sentiment analysis has great importance in fake review detection system. This paper introduces a sentiment analysis model that can separate positive and negative sentimental reviews efficiently. It shows an analysis of sentiment distribution for fake and truthful reviews. Also, the proposed sentiment model is used to find the impact of probabilistic sentiment score in fake online review detection using a hotel review dataset.
Topics & Concepts
Sentiment analysisComputer scienceProbabilistic logicTopic modelData scienceAdvertisingArtificial intelligenceBusinessSpam and Phishing DetectionSentiment Analysis and Opinion MiningNetwork Security and Intrusion Detection