In this paper, we present Cdear, a novel system to detect fake reviews by using sentiment analysis on attributes of products. We formulate review spam detection as an opinion coincided problem. Specifically, we try to capture the sentiment diverse of attributes of products among different consumers. To our knowledge, this is the very first attempt to use sentiment analysis on attributes of products in reviews to detect review spam. To evaluate the effectiveness of our system, we conduct the experiments on the real life datasets and employ 20 experts to assess the reliability of reviews by carrying out a simulation of shopping online. Meanwhile, we developed an evaluation system to help those experts to assess the reviews, thus to ensure the scientificity of experiments. Comparison between the automatic results of proposed system and human evaluated results demonstrates that the sentiment-based method matches approximately with human perception of reviews' reliability with 82.66% accuracy.
['Aakas Zhiyuli', 'Xun Liang', 'Yige Wang']
Discerning the Trend: Concealing Deceptive Reviews