Deceptive Opinion Spam based On Deep Learning

Abstract

The revolution of web technologies and e-commerce platforms such as Amazon and eBay have promoted the businesses and have become essential in our daily life. Despite that these tools have helped the ease of purchases, there is a lot of scams in these kinds of technologies. Unfortunately, several companies use fake opinions to influence the customers about buying a product or to demote the competitors’ one. The detection of deceptive opinion spam is a hard task because of the way it is written. The majority of existing deceptive opinion detection models focus on machine learning with hand-engineered feature extraction. Unfortunately, these architectures do not provide the semantic information of the reviews, which is the key to the detection of deceptive opinions. In this paper, we address the comparison between the different neural network architectures and their effectiveness in the detection of deceptive opinion spam. The results show that Convolutional Neural Networks perform better compared to other models.