A Status Property Classifier of Social Media User's Personality for Customer-Oriented Intelligent Marketing Systems: Intelligent-Based Marketing Activities

Tsung-Yi Chen, Yuh-Min Chen and Meng-Che Tsai
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Tsung-Yi Chen: Nanhua University, Chiayi County, Taiwan
Yuh-Min Chen: National Cheng Kung University, Tainan City, Taiwan
Meng-Che Tsai: National Cheng Kung University, Tainan City, Taiwan

International Journal on Semantic Web and Information Systems (IJSWIS), 2020, vol. 16, issue 1, 25-46

Abstract: Enterprises need to obtain information about not only specific customer preferences, but also, more importantly, customers' psychological characteristics that significantly influence their consumption behaviors and response to intelligent-based marketing activities. If enterprises want to implement more precise intelligent selling activities for customers, customers' personality information will serve as a highly valued reference. The automatic detection method proposed in this study is based on techniques such as text semantic mining and machine learning to conduct personality type prediction on the target by collecting and analyzing the target's social media data. In the test, 5,858 statuses were obtained, 815 of which were labeled, with 122 effective tags. In general, when n = 5, the labeling rate can reach 60-80%. The status property classifier (SPC) proposed in this study can predict the personality type (PT) of the user publishing the status set with a high degree of accuracy by conducting text semantic mining on the status set.

Date: 2020
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