Using supervised learning to classify authentic and fake online reviews

• Main Authors: Banerjee, Snehasish, Chua, Alton Yeow Kuan, Kim, Jung-Jae
• Other Authors: Wee Kim Wee School of Communication and Information
• Format: Conference or Workshop Item
• Language: English
• Published: 2015
• Subjects: DRNTU::Library and information science::Libraries::Information systems; DRNTU::Social sciences::Communication::Communication theories and models
• Online Access: https://hdl.handle.net/10356/107209; http://hdl.handle.net/10220/25330; http://dx.doi.org/10.1145/2701126.2701130
• Institution: Nanyang Technological University

Before making a purchase, users are increasingly inclined to browse online reviews that are posted to share post-purchase experiences of products and services. However, not all reviews are necessarily authentic. Some entries could be fake yet written to appear authentic. Conceivably, authentic and f...