Abstract
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.
Highlights
The rapid development of e-commerce has deeply influenced the behavior pattern of consumers, and online shopping has become the normal way of shopping for web users currently
Based on the sentiment analysis technology, this paper directly explores the consumers’ sentimental orientation to the attributes of commodity or service from comments text, analyzes the user satisfaction and preference, and discusses how the consumers, commodity producers and online shopping platforms to manage and utilize online reviews effectively
This paper explains how to perform the users’ sentiment analysis of shopping websites based on online reviews. It describes the research background and literature review on sentimental polarity analysis of online reviews and its value mining; it explains the research process of sentimental polarity analysis and how to collect and process data, preprocess text content, extract the main attributes of commodity or service, and identify the relationship between attributes and emotional words; and it provides the reference for consumers, commodity producers and online shopping platforms according to analysis results; at the end of the full text, it comes up with the foresight and future work
Summary
The rapid development of e-commerce has deeply influenced the behavior pattern of consumers, and online shopping has become the normal way of shopping for web users currently. The shopping experience of other consumers will have an important impact on their purchasing decisions. Users’ sentimental orientation of online reviews can have a greater impact on the consumption psychology and purchasing decisions of potential users [3]. Online reviews include a large amount of information about the description and use feeling of commodity attributes, as well as consumers’ feedback on commodity or service. How to analyze the sentimental orientation of these rich and complex online reviews and mine the hidden rule, in order to better provide decision-making basis for consumers, enterprises and shopping platform. Based on the sentiment analysis technology, this paper directly explores the consumers’ sentimental orientation to the attributes of commodity or service from comments text, analyzes the user satisfaction and preference, and discusses how the consumers, commodity producers and online shopping platforms to manage and utilize online reviews effectively
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