Sentimental Analysis of Online Reviews of Egg Consumption Based on DSLML

被引:0
作者
Bao Q. [1 ]
Li J. [1 ]
Shi S. [1 ]
Dai Y. [1 ]
Liu X. [1 ]
机构
[1] College of Information and Electric Engineering, China Agricultural University, Beijing
来源
Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery | 2021年 / 52卷
关键词
Domain sentimental lexicon; Egg; LDA theme model; Online reviews; Sentiment analysis; Sentimental classification of tendency;
D O I
10.6041/j.issn.1000-1298.2021.S0.063
中图分类号
学科分类号
摘要
With the rapid development of information technology, packaging and logistics technology, the range and scale of E-commerce products, including agricultural products, are getting larger and larger. At the same time, the online shopping review data has grown exponentially.The online reviews has become a hotspot. Taking JD's E-commerce platform as an example, the online reviews were mined out and the sentimental tendency of consumers about eggs consumption was analyzed deeply. The main research contents included proposing a domain sentimental lexicon with machine learning (DSLML) classification method. The semantic orientation pointwise mutual information (SO-PMI) method was used to construct the domain sentimental lexicon, and then a machine learning model was selected as the classifier to achieve the classification of sentimental orientation of online egg reviews. Then the LDA topic model was constructed to mine out the positive and negative topics in egg reviews. The experimental results showed that the DSLML classification model was improved in each indicator of text sentimental tendency classification, compared with machine learning models and domain sentimental lexicon (DSL) alone. From the results of the theme mining, the quality of eggs and the packaging of goods were the two aspects that consumers mostly concerned about. The conclusion of this research can provide data support and theoretical support for egg E-commerce operators to improve business strategies and service quality. © 2021, Chinese Society of Agricultural Machinery. All right reserved.
引用
收藏
页码:496 / 503
页数:7
相关论文
共 38 条
  • [1] YIN Lichun, WANG Yue, Influencing factors and mechanism of book consumer satisfaction based on online comments, Library and Information Service, 63, 22, pp. 106-117, (2019)
  • [2] 5, pp. 51-52, (2018)
  • [3] 3, pp. 142-156, (2019)
  • [4] LI Ran, LIN Zheng, LIN Hailun, Et al., Text emotion analysis: a survey, Journal of Computer Research and Development, 55, 1, pp. 30-52, (2018)
  • [5] HEMMATIAN F, SOHRABI M K., A survey on classification techniques for opinion mining and sentiment analysis, Artificial Intelligence Review, 52, 3, pp. 1495-1545, (2019)
  • [6] LIU Z, WANG Y, CHEN T., Audio feature extraction and analysis for scene segmentation and classification, The Journal of VLSI Signal Processing, 20, 1-2, pp. 61-79, (1998)
  • [7] ZUO Shaoze, Text mining for online purchase of comment data: take the review of a refrigerator as an example, (2019)
  • [8] GAO Simeng, Sentiment analysis for elderly mobile phone users based on machine learning, (2019)
  • [9] HUANG Wenbo, The analysis and application of user comments base on E-commemerce, (2020)
  • [10] DASGUPTA S, SENGUPTA K., Analyzing consumer reviews with text mining approach, Paradigm, 20, 1, pp. 56-68, (2016)