Abstract
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 fake reviews are not easy to differentiate. Hence, this paper uses supervised learning algorithms to analyze the extent to which authentic and fake reviews could be distinguished based on four linguistic clues, namely, understandability, level of details, writing style, and cognition indicators. The model performance was compared with two baselines. The results were generally promising.
| Original language | English |
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| Pages | 1-7 |
| Number of pages | 8 |
| Publication status | Published - 2015 |
| Event | International Conference on Ubiquitous Information Management and Communication - Bali, Indonesia Duration: 8 Jan 2015 → 10 Jan 2015 https://dl.acm.org/citation.cfm?id=2701126 |
Conference
| Conference | International Conference on Ubiquitous Information Management and Communication |
|---|---|
| Country/Territory | Indonesia |
| City | Bali |
| Period | 8/01/15 → 10/01/15 |
| Internet address |