1
School of Engineering Science, College of Engineering, University of Tehran, Tehran, Iran
2
University of Tehran, College of Engineering, School of Engineering Science, Tehran, Iran.
10.22059/jac.2022.90383
Abstract
One important criterion in decision-making when we want to purchase a product or a service is users’ reviews. When something is valuable, it’s fake and will be created as well. It is the same for users’ reviews. The purpose of these fake reviews is to deceive users, leading them to make a wrong choice. One challenging problem is when we can trust a review. Although many researchers attempted to address this problem, none of them pictured the problem in a streaming domain. With the help of the review network’s properties, we propose a model to find reliable reviews when reviews are coming in a stream. Our model is fast and online, that is, it is capable of identifying reliable reviews as they are been submitted, and scalable because it is a complementary model to offline models in detecting fake reviews.
Ghodsi, S., & Moieni, A. (2022). Opinion Fraud Detection in Streaming Comments Utilising Node Similarity in the Review Network. Journal of Algorithms and Computation, 54(2), 21-35. doi: 10.22059/jac.2022.90383
MLA
Shahab Ghodsi; Ali Moieni. "Opinion Fraud Detection in Streaming Comments Utilising Node Similarity in the Review Network". Journal of Algorithms and Computation, 54, 2, 2022, 21-35. doi: 10.22059/jac.2022.90383
HARVARD
Ghodsi, S., Moieni, A. (2022). 'Opinion Fraud Detection in Streaming Comments Utilising Node Similarity in the Review Network', Journal of Algorithms and Computation, 54(2), pp. 21-35. doi: 10.22059/jac.2022.90383
VANCOUVER
Ghodsi, S., Moieni, A. Opinion Fraud Detection in Streaming Comments Utilising Node Similarity in the Review Network. Journal of Algorithms and Computation, 2022; 54(2): 21-35. doi: 10.22059/jac.2022.90383
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