scholarly journals A Survey on Different Techniques for Product Fake Review Detection and Product Rating

2021 ◽  
Author(s):  
Adnan Telwala ◽  
Ayush Pratap ◽  
Ketan Gaikwad ◽  
Tushar Chaudhari ◽  
Sukhada Bhingarkar
Keyword(s):  
Sentiment Analysis ◽  
Text Analysis ◽  
Work Force ◽  
Research Direction ◽  
Product Reviews ◽  
Online Business ◽  
Product Rating

Numerous online business sites empower the customers to create a product reviews along with feedback in the shape of ratings. This gives the organization work force a sign about their items’ remaining on the lookout, while likewise empowering individual customer to frame an assessment and help buy an item. As of late, Sentiment Analysis (SA) has gotten quite possibly interesting due to the potential business advantages of text analysis. One of the most important problems in confronting SA is the manner by which to remove feelings in the assessment, as well as how to identify counterfeit good reviews and negative surveys derived from assessment surveys. Besides, the assessment surveys acquired from clients can divided into two categories: positive and negative, which can be utilized by a shopper to choose an item. In this survey, we have thoroughly discussed about fake review detection of products as well as product rating by different SA techniques. Further, we have discussed the research direction in fake review detection and product rating.

scholarly journals Examining Hidden Meaning of E-commerce Platform

2019 ◽  
Vol 8 (12) ◽  
pp. 257-261
Keyword(s):  
Decision Making ◽  
Sentiment Analysis ◽  
Food Products ◽  
Product Reviews ◽  
Specific Time ◽  
High Importance ◽  
Customer Reviews ◽  
Time Period ◽  
Emotion Lexicon ◽  
Product Rating

Different e-commerce companies try to maintain high importance for their customer satisfactions. It helps them to understand the performance of their products. Nowadays customers trust on the product reviews while shipping online. But it is a cumbersome task to handle millions of customer reviews within specific time period. Due to this problem consumers usually follow the set of reviews before taking decision for purchasing any products from online. Although, each consumer rates the product from 1 to 5 stars, these overall product rating judge products towards their customers satisfaction. Consumers also provide a text based summary as a review of their experiences and opinions about the products. Customer sentiment analysis is a method to process these customer reviews to summarize different products. In this manuscript, we analyzed the text summery of Amazon food products using NRC Emotion Lexicon to determine the overall responses of the products using eight emotions of the customers. Our result can be used to take further decision making for the future of the products.

scholarly journals RoBERTa-IAN for aspect-level sentiment analysis of product reviews

2021 ◽  
Vol 1827 (1) ◽  
pp. 012079
Author(s):  
Jingrui Dai ◽  
Fang Pan ◽  
Zhaoyu Shou ◽  
Huibing Zhang
Keyword(s):  
Sentiment Analysis ◽  
Product Reviews

scholarly journals Unpacking the Quantifying and Qualifying Potential of Semi-Open Job Satisfaction Questions through Computer-Aided Sentiment Analysis

2021 ◽  
Author(s):  
Indy Wijngaards ◽  
Martijn Burger ◽  
Job van Exel
Keyword(s):  
Job Satisfaction ◽  
Sentiment Analysis ◽  
Text Analysis ◽  
Discriminant Validity ◽  
Added Value ◽  
Information Richness ◽  
Convergent And Discriminant Validity ◽  
Computer Aided ◽  
Satisfaction Question ◽  
Open Question

AbstractDespite their suitability for mitigating survey biases and their potential for enhancing information richness, open and semi-open job satisfaction questions are rarely used in surveys. This is mostly due to the high costs associated with manual coding and difficulties that arise when validating text measures. Recently, advances in computer-aided text analysis have enabled researchers to rely less on manual coding to construct text measures. Yet, little is known about the validity of text measures generated by computer-aided text analysis software and only a handful of studies have attempted to demonstrate their added value. In light of this gap, drawing on a sample of 395 employees, we showed that the responses to a semi-open job satisfaction question can reliably and conveniently be converted into a text measure using two types of computer-aided sentiment analysis: SentimentR, and Linguistic Inquiry and Word Count (LIWC) 2015. Furthermore, the substantial convergence between the LIWC2015 and, in particular, SentimentR measure with a closed question measure of job satisfaction and logical associations with closed question measures of constructs that fall within and outside job satisfaction’s nomological network, suggest that a semi-open question has adequate convergent and discriminant validity. Finally, we illustrated that the responses to our semi-open question can be used to fine-tune the computer-aided sentiment analysis dictionaries and unravel antecedents of job satisfaction.

Sentiment Analysis of Kaspi Product Reviews

2021 ◽  
Author(s):  
Yerassyl Kelsingazin ◽  
Iskander Akhmetov ◽  
Alexander Pak
Keyword(s):  
Sentiment Analysis ◽  
Product Reviews
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