在线社交网络中服装品牌信息主题挖掘及其指标构建

Topic mining and index system of clothing brand information in online social network

为深入探究在线社交网络中服装品牌信息传播主题及其内涵,首先通过选择性接触理论分析消费者接触信息时的心理过程,然后运用数据挖掘和隐含狄利克雷分布(Latent Dirichlet Allocation,LDA)主题模型,从大量在线社交网络的服装品牌文本数据中挖掘服装品牌信息主题,再运用扎根分析方法提炼出服装品牌信息指标体系。最终形成的服装品牌信息指标体系包括产品信息、服务信息、营销信息、口碑信息、企业信息和环境信息6个维度和产品属性、售前服务、广告营销、企业形象等13个指标,并提出针对性的服装品牌信息设计和传播建议。研究结果可为服装企业在社交网络中传播符合消费者需求的服装品牌信息提供参考。

In order to deeply explore the indicator system of online social network clothing brand information,the psychological process of consumer contact information is first analyzed through selective contact theory,and then the data mining and LDA theme model are used to excavate the clothing brand information theme from the clothing brand text data of a large number of online social networks,and then the root analysis method is used to extract the clothing brand information index system.Finally,a clothing brand information index system is formed,including 6 dimensions of product information,service information,marketing information,word-of-mouth information,corporate information and environmental information,and 13 indicators such as product attributes,pre-sales services,advertising and marketing,corporate image,etc.,and puts forward targeted clothing brand information design and communication strategies.The results of the study can provide a reference for clothing brand companies to disseminate clothing brand information that meets consumer needs in social networks.