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oai:gredos.usal.es:10366/1433062025-06-05T12:36:20Zcom_10366_142734com_10366_122682com_10366_4666com_10366_3823col_10366_143142

Hussain, Naveed Mirza, Hamid Turab Hussain, Ibrar 2020-06-23T11:12:08Z 2020-06-23T11:12:08Z 2019-03-14 ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 8 (2019) 2255-2863 http://hdl.handle.net/10366/143306 Online reviews about the purchase of a product or services provided have become the main source of user opinions. To gain profit or fame usually spam reviews are written to promote or demote some target products or services. This practice is known as review spamming. In the last few years, different methods have been suggested to solve the problem of review spamming but there is still a need to introduce new spam review detection method to improve accuracy results. In this work, researchers have studied six different spammer behavioral features and analyzed the proposed spam review detection method using weight method. An experimental evaluation was conducted on a benchmark dataset and achieved 84.5% accuracy. application/pdf eng Ediciones Universidad de Salamanca (España) info:eu-repo/semantics/openAccess info:eu-repo/semantics/openAccess Computación Informótica Computing Information Technology Detecting Spam Review through Spammer’s Behavior Analysis info:eu-repo/semantics/article