The Perception of Usefulness: Iranian Customers' Evaluation of Customer Reviews

Over the last decade, the retail industry has had a phenomenal growth. All figures show their success and efficiency and many studies have shown the role of customer reviews in encouraging ambivalent purchasers to buy items online. There have been numerous studies on why people read and trust these comments and taking for granted the important role of customer reviews in determining buying decision, this study endeavors to identify and explain the different factors involved in making a comment "useful". We took an Iranian retail website and collected comments on perceived "usefulness" of each review. Our results showed that perceived level of usefulness was related to the word count of the comments, personal experience of the writer with the product, emotional description of the product, and mentioning the strength/weakness points of the product

Creating and detecting fake reviews of online products

Customers increasingly rely on reviews for product information. However, the usefulness of online reviews is impeded by fake reviews that give an untruthful picture of product quality. Therefore, detection of fake reviews is needed. Unfortunately, so far, automatic detection has only had partial success in this challenging task. In this research, we address the creation and detection of fake reviews. First, we experiment with two language models, ULMFiT and GPT-2, to generate fake product reviews based on an Amazon e-commerce dataset. Using the better model, GPT-2, we create a dataset for a classification task of fake review detection. We show that a machine classifier can accomplish this goal near-perfectly, whereas human raters exhibit significantly lower accuracy and agreement than the tested algorithms. The model was also effective on detected human generated fake reviews. The results imply that, while fake review detection is challenging for humans, “machines can fight machines” in the task of detecting fake reviews. Our findings have implications for consumer protection, defense of firms from unfair competition, and responsibility of review platforms.</p