Incorporating Social Network Thai Text Mining with Lifestyle Segmentation Analysis

被引:0
|
作者
Ratanasawadwat, Nitipan [1 ]
Jiamthapthaksin, Rachsuda [2 ]
机构
[1] Assumption Univ, Dept Mkt, Bangkok, Thailand
[2] Assumption Univ, Dept Comp Sci, Bangkok, Thailand
关键词
Lifestyle Segmentation; k-means Clustering; Social Network Text Mining; Latent Dirichlet Allocation; Social Interests;
D O I
10.1109/IIAI-AAI.2017.213
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Due to popularity of social networks, smartphones and mobile Internet usage in Thailand, Thai people, especially young adults have been utilizing social network such as Facebook on the move via their smartphone in daily basis. The study proposes a framework that are attempting to incorporate social network Thai text data with online marketing survey using computer-assisted self-interview questionnaire in order to develop better, information-richer marketing segmentation. The merits of the study are to reduce manpower and errors in traditional offline survey, to offer easier access to the young adults, to retrieve and utilize social network data by combining them with lifestyle factors to develop market segmentation with better understanding of the sophisticated customers.
引用
收藏
页码:971 / 975
页数:5
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