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دسته بندی:
تجارت الکترونیک - electronic commerce
سال انتشار:
2018
عنوان انگلیسی مقاله:
Topic analysis of online reviews for two competitive products using latent Dirichlet allocation
ترجمه فارسی عنوان مقاله:
تحلیل موضوعی بازدیدهای آنلاین برای دو محصول رقابتی با استفاده از تخصیص نهان دیریکله
منبع:
Electronic Commerce Research and Applications Volume 29, May–June 2018, Pages 142-156
نویسنده:
Wenxin Wang, Yi Feng, Wenqiang Dai
چکیده انگلیسی:
The voice of the customer plays an important role in product competition. Traditional methods in the area have largely focused on market research and questionnaire surveys to obtain customer preferences. However, online product reviews have provided a good and reliable channel for not only understanding customers needs for one product or service but also analyzing products’ competition in the market. In this paper, we propose a new framework of applying online product reviews to analyze customer preferences for two competitive products. We extract the key topics of online reviews for two specific competitive products via a text mining approach of latent Dirichlet allocation (LDA). Topic difference analysis demonstrates the unique topics of the two products. The relative importance and topic heterogeneity analyses identify the competitive superiorities and weaknesses of both products. Two case studies that are presented demonstrate the efficacy of the proposed framework. The method also provides valuable managerial implications for product designers and e-commerce companies.
keywords: Competitive analysis |Latent Dirichlet allocation |Online product reviews |Product competition |Text mining |Topic analysis
قیمت: رایگان
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