The Effect of Text Preprocessing Strategies on Detecting Fake Consumer Reviews

Author(s):  
Aliaksandr Barushka ◽  
Petr Hajek
2021 ◽  
pp. 002224372110202
Author(s):  
Shrabastee Banerjee ◽  
Chris Dellarocas ◽  
Georgios Zervas

This article studies the question and answer (Q&A) technology of electronic commerce platforms, an increasingly common form of user-generated content that allows consumers to publicly ask product-specific questions and receive responses, either from the platform or from other customers. Using data from a major online retailer, the authors show that Q&As complement consumer reviews: unlike reviews, questions are primarily asked pre-purchase and focus on clarification of product attributes rather than discussion of quality; answers convey fit-specific information in a predominantly sentiment-free way. Based on these observations, the authors hypothesize that Q&As mitigate product fit uncertainty, leading to better matches between products and consumers, and therefore improved product ratings. Indeed, when products suffering from fit mismatch start receiving Q&As, their subsequent ratings improve by approximately 0.1 to 0.5 stars and the fraction of negative reviews that discuss fit-related issues declines. The extent of the rating increase due to Q&As is proportional to the probability that purchasers will experience fit mismatch without Q&A. These findings suggest that, by resolving product fit uncertainty in an e-commerce setting, the addition of Q&As can be a viable way for retailers to improve ratings of products that have incurred low ratings due to customer-product fit mismatch.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mehdi Srifi ◽  
Ahmed Oussous ◽  
Ayoub Ait Lahcen ◽  
Salma Mouline

AbstractVarious recommender systems (RSs) have been developed over recent years, and many of them have concentrated on English content. Thus, the majority of RSs from the literature were compared on English content. However, the research investigations about RSs when using contents in other languages such as Arabic are minimal. The researchers still neglect the field of Arabic RSs. Therefore, we aim through this study to fill this research gap by leveraging the benefit of recent advances in the English RSs field. Our main goal is to investigate recent RSs in an Arabic context. For that, we firstly selected five state-of-the-art RSs devoted originally to English content, and then we empirically evaluated their performance on Arabic content. As a result of this work, we first build four publicly available large-scale Arabic datasets for recommendation purposes. Second, various text preprocessing techniques have been provided for preparing the constructed datasets. Third, our investigation derived well-argued conclusions about the usage of modern RSs in the Arabic context. The experimental results proved that these systems ensure high performance when applied to Arabic content.


2021 ◽  
Vol 13 (4) ◽  
pp. 2024
Author(s):  
Do-Hyung Park

Today, consumer-created information such as online consumer reviews have become important and popular, playing a key role in consumer decision making. Compared with expert-created information, each piece of information is less powerful or persuasive, but their aggregation can be more credible and acceptable. This concept is called collective intelligence knowledge. This study focuses on the persuasive effect on consumer product attitudes of consumer-created information compared to expert-created information. Using source credibility and familiarity theory, the study reveals how prior brand attitudes can play a moderating role in the persuasive effect of consumer-created information and expert-created information. Specifically, this study shows how consumer-created information is more persuasive when consumers have more favorable prior brand attitudes, while expert-created information is more persuasive when consumers have less favorable prior brand attitudes. Based on the results, this study proposes practical strategies for information structure, curation, and presentation. If a company has a good-quality brand evaluation of its products, it should increase the weight of consumer-created information such as online consumer reviews. Otherwise, the company needs to first improve brand evaluation through expert-created information such as third-parties or power-blogger reviews.


Author(s):  
Murugan Anandarajan ◽  
Chelsey Hill ◽  
Thomas Nolan
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