文章基本信息

标题：Automatic Generation of Product Association Networks Using Latent Dirichlet Allocation
本地全文：下载
作者：Javier Sanchez-Monzon ; Javier Sanchez-Monzon ; Johannes Putzke 等
期刊名称：Procedia - Social and Behavioral Sciences
印刷版ISSN：1877-0428
出版年度：2011
卷号：26
页码：63-75
DOI：10.1016/j.sbspro.2011.10.563
语种：English
出版社：Elsevier
摘要：AbstractWe present a method for extracting semantic networks of words that consumers associate with products and brands, and illustrate the method using reviews of McDonald's products from the opinion platform www.ciao.de as examples. We model the generation of each product review with the probabilistic topic model Latent Dirichlet Allocation (LDA), which enables us to discover the hidden thematic structure of all the reviews in our text collection. We conduct an association analysis of all the words used, revealing the semantic networks of words. Our approach may be highly relevant for marketing managers, for example, as they analyze brand concept maps or seek to optimize ad campaigns with the best words.
关键词：brand concept maps;collaborative innovation networks;data mining;social networks;webmining;COINs;LDA