Devising a Cross Domain Algorithm to Detect Deceptive Review Comments with S-O-R Framework(2/3)

Project Details


E-commerce has been developed at the high pace in recent years. Accordingly, the rise of potential spamming reviews from the online services is growing quickly and attract significant concern from many organizations. Therefore, deceptive detection is one of critical issues in online businesses. Existing studies investigated deceptive detection mainly base on the technology of traditional text mining. As a result, the detection is closely related to the training corpus collected. However, reviews for different application domains utilize very different words. As the result, the precision and accuracy of these approaches were less than ideal when being applying to different domains. In this study, a cross domain detector is designed by utilizing the Stimulus–Organism–Response (S-O-R) framework to infer word categories. The proposed approach will be intensively evaluated with the three benchmark datasets comprised by previous research to compare the performance with the state of the art approaches.
Effective start/end date1/08/2031/07/21


  • Deceptive reviews detection
  • Stimuli-Organism-Response (S-O-R) framework


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