Research On Online Review Based On LDA Subject Model

• Published in: International journal of advanced networking and applications Vol. 12; no. 3; pp. 4606 - 4612
• Main Authors: Tao, Guo, Shi-qi, Wu, Yi-Cheng, Shi, Qian-Qian, Ma, Zhi-hang, Tang
• Format: Journal Article
• Language: English
• Published: Eswar Publications 01.11.2020
• Subjects: Algorithms; Consumers; Consumption; Customer services; Customers; Decision making; Dynamic models; Electronic commerce; Frequency analysis; Graphical representations; Language; Natural language processing; Semantics; Visualization
• ISSN: 0975-0290; 0975-0282
• DOI: 10.35444/IJANA.2020.12306

The text topic analysis is the core element of the comprehensive review of clothing products, which can directly understand the views and consumption trends of consumer groups, taking a brand clothing store in JD.com as the research object, by using Python crawler and HANLP natural language processing technology, seven of the top-selling fashion reviews were classified and analyzed. Word frequency statistics, TF-IDF and other methods were used to quantify the text, this paper uses the visualization techniques such as word cloud graph contrast, pyLDAvis dynamic model and Sankey graph to display customers' attention points and real shopping needs from various angles. The experimental results show that the visual results of online review research based on the theme model of Lda can clearly show the advantages and disadvantages of customer-centered evaluation and clothing, and provide important reference for merchants to improve decision-making and optimize service.