| Opinion Fraud Detection in Streaming Comments Utilizing Node Similarity in the Review Network |
| کد مقاله : 1020-CSANS2022 (R2) |
| نویسندگان: |
|
شهاب قدسی1، دکتر علی معینی *2 1دپارتمان الگوریتم و محاسبات، دانشکده علوم مهندسی، دانشکدگان فنی، دانشگاه تهران، تهران، ایران 2دپارتمان الگوریتم و محاسبات، دانشکده علوم مهندسی،دانشکدگان فنی، دانشگاه تهران، تهران، ایران |
| چکیده مقاله: |
| Due to the exponential growth of electronic commerce, online shopping has become a part of our lives. 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 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. |
| کلیدواژه ها: |
| big data; opinion fraud; network science; review spam; spark; fake reviews; streaming data |
| وضعیت : مقاله برای ارائه شفاهی پذیرفته شده است |
