Open Access
Subscription Access
Research on Influencing Factors of Garment Commodity Bad Reviews Based on LDA Theme Model
The rise of e-commerce platform makes more consumers buy clothing goods online. However, due to the specific transaction process of online shopping, consumers are prone to generate various complaints and dissatisfaction, and thus conduct negative comments. Therefore, it is of great significance for apparel e-commerce to improve the quality of goods and services and improve user satisfaction to find out the reasons for consumers' dissatisfaction with clothing products from a large number of bad reviews. The article takes the poor evaluation data of affordable clothing brands and luxury clothing brands on the JD platform as the research object, conducts word frequency statistics and LDA theme model analysis on the poorly reviewed texts, and believes that the main factors affecting the poor evaluation of clothing products are Commodity Quality, Customer Service, Merchant Integrity, and Logistics Speed. In addition, by comparing and analyzing the difference evaluation data of the two types of clothing brands, it can be found that the most important influencing factor of affordable clothing brands is Commodity Quality, while the most important factor of the difference evaluation of luxury clothing brands is Customer Service.
Keywords
Bad Reviews, Influencing Factors, Text Mining, Lda Topic Model.
User
Font Size
Information
- China Netcom . CNNIC released the 47th Statistical Report on China's Internet Development [EB/OL]2021-02-03[2022-03-12].http://www.cac.go v.cn/2021-02/03/c_1613923423079314.htm.
- Prospective Industry Research Institute. Analysis of the current situation and development trend of the clothing retail industry in 2019. The proportion of per capita clothing consumption expenditure of residents is decreasing year by year [EB/OL]2019-07-31[2022-03-12]. https: //www. qianzhan.com/analyst/detail/220/19073145402346.ht ml.
- Wu Zhenghong. The trend of socialized, fan-based and content-based operation -- the new model of clothing marketing in the era of e-commerce 2.0 [J]. China Textile, 2016 (08): 98-100
- Fan Z P , Che Y J , Chen Z Y . Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis[J]. Journal of Business Research, 2017, 74(May):90-100.
- Hennig-ThurauT , Malthouse E C , Friege C , et al. The Impact of New Media on Customer Relationships[J]. Journal of Service Research, 2010, 26(3):311-330.
- Yin Guo-peng . What online reviews do consumers think are more useful—— The effect of social factors [J] Managing the World, 2012 (12): 10.
- Chevalier J A , Mayzlin D . The Effect of Word of Mouth on Sales: Online Book Reviews[J]. Journal of Marketing Research (JMR), 2006, 43(3):345-354.
- Casalo L V , Flavian C , Guinaliu M , et al. Avoiding the dark side of positive online consumer reviews: Enhancing reviews' usefulness for high risk-averse travelers[J]. Journal of Business Research, 2015, 68(9):1829-1835.
- Rohini A ,Burnkrant R E , Rao U H . Consumer Response to Negative Publicity: The Moderating Role of Commitment[J]. Journal of Marketing Research, 2000.
- Jabr W , Zheng Z E . Know Yourself and Know Your Enemy: An Analysis of Firm Recommendations and Consumer Reviews in a Competitive Environment[J]. Mis Quarterly, 2014, 38(3):635-654.
- Lu Hai-xia, Wu Xiao-ding, Su Li-xun. On The Effect of Negative Online Customer Review on Purchase Behavior [J] . Beijing Sociology, 2014 (05): 102-109.
- Wang Y, Wang WJ, Liu ZY. A study on the influence of online negative review information on potential consumers' purchase intention[J]. Intelligence Science, 2018, 36(10):8.
- Kim Y , Chang Y , Wong S F , et al. Customer attribution of service failure and its impact in social commerce environment[J]. International Journal of Electronic Customer Relationship Management, 2014, 8(1/2/3):136.
- Li M. Analysis of poor book reviews in online bookstores and its insights[J]. Library Journal, 2012, 32(09): 58-61+94.
- Bi DAT, Chu QH, Cao Ran. A study on the factors influencing consumers' willingness to give bad reviews based on text mining[J]. Intelligence Theory and Practice, 2020, 43(10): 137-143.
- Cao Jun,Wang Hu. Research on factors influencing poor reviews of takeaway users - based on text reviews and Word2vec [J]. Modern commerce industry,2017,38(2):55-56.
- Sun QY, Liu JH. A study on the influencing factors of MOOC poor evaluation intention based on text mining[J]. Statistics and Management,2021,36(9):105-112.
- Mehta M P , Kumar G , Ramkumar M . Customer expectations in the hotel industry during the COVID-19 pandemic: a global perspective using sentiment analysis[J]. Tourism Recreation Research, 2021:1-18.
- GangadharanV , Gupta D . Recognizing Named Entities in Agriculture Documents using LDA based Topic Modelling Techniques[J]. Procedia Computer Science, 2020, 171:1337-1345.
- Yang Fan. Research on Online Reviews Clustering Based on LDA Topic Model[D]. Dalian University of Technology.
- Guo T , Wu S Q , Shi Y C , et al. Research On Online Review Based On LDA Subject Model[J]. International Journal of Advanced Networking and Applications - IJANA, 2020(03).
Abstract Views: 118
PDF Views: 0