A unified framework for reviewer reputation estimation in online review systems

Individuals and organizations widely use product reviews for their decision making. But most of the review systems pay less attention on verifying the identity of reviewers and the content of reviews. This leads to the presence of uninformative, biased or even false information. Also some people attempt to control the system by opinion spamming such as writing fake reviews to promote or demote some target products. If reviewer reputation can be measured, the consumers can find reviews that reflect genuine user experiences and opinions, depending on the reviews from reputed reviewers. This paper presents a reputation model devised to measure reviewer reputation in online review systems based on the source credibility which is defined as expertise and trustworthiness. Our experimental results show that the proposed reputation model is effective in measuring reputation. The model outperforms existing methods in measuring the reputation of reviewers. The model is simple and applicable to most of the online review systems.