<abstract xmlns="http://www.w3.org/1999/xhtml"><p>With the rapid development of online shopping, how to explore the value of online reviews, so as to give full play to their role in potential users’ purchasing decisions. Based on text mining and quantitative analysis, this paper studies the sentiment analysis of online reviews on B2C shopping website. The main attributes of commodity or service are extracted based on the order of word frequency in the online reviews. Text analysis method is used to judge the relationship between attributes of commodity or service and its emotional words. The fine-grained sentimental polarity and intensity of attributes are identified to analyze users’ concerns and preferences. The research shows that users pay more attention to the configuration and after-sales service of mobile, and have a positive sentimental orientation to most of attributes, especially unlocking function, hand feeling attribute and logistics service; and have a neutral sentimental orientation towards the attributes of battery and memory, and a negative sentimental orientation towards the membrane of mobile phone. The results can provide a reference for consumers to make purchasing decisions, for enterprises to improve product quality, and for shopping platform to optimize service.</p></abstract>

With the rapid development of online shopping, how to explore the value of online reviews, so as to give full play to their role in potential users’ purchasing decisions. Based on text mining and quantitative analysis, this paper studies the sentiment analysis of online reviews on B2C shopping website. The main attributes of commodity or service are extracted based on the order of word frequency in the online reviews. Text analysis method is used to judge the relationship between attributes of commodity or service and its emotional words. The fine-grained sentimental polarity and intensity of attributes are identified to analyze users’ concerns and preferences. The research shows that users pay more attention to the configuration and after-sales service of mobile, and have a positive sentimental orientation to most of attributes, especially unlocking function, hand feeling attribute and logistics service; and have a neutral sentimental orientation towards the attributes of battery and memory, and a negative sentimental orientation towards the membrane of mobile phone. The results can provide a reference for consumers to make purchasing decisions, for enterprises to improve product quality, and for shopping platform to optimize service.

Users’ Sentiment Analysis of Shopping Websites Based on Online Reviews

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Users\u2019 Sentiment Analysis of Shopping Websites Based on Online Reviews"}

With the rapid development of online shopping, how to explore the value of online reviews, so as to give full play to their role in potential users’ purchasing...

Users’ Sentiment Analysis of Shopping Websites Based on Online Reviews

Data publikacji: 20 sie 2020

Zakres stron: 493 - 502

Otrzymano: 05 gru 2019

Przyjęty: 01 lut 2020

DOI: https://doi.org/10.2478/amns.2020.2.00026

Słowa kluczowe
online review, shopping website, sentiment analysis, text mining, sentimental polarity

© 2020 Xiaohong Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Users’ Sentiment Analysis of Shopping Websites Based on Online Reviews

Data publikacji: 20 sie 2020

Zakres stron: 493 - 502

Otrzymano: 05 gru 2019

Przyjęty: 01 lut 2020

DOI: https://doi.org/10.2478/amns.2020.2.00026

Słowa kluczoweonline review, shopping website, sentiment analysis, text mining, sentimental polarity

© 2020 Xiaohong Wang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
online review, shopping website, sentiment analysis, text mining, sentimental polarity