TY - JOUR
T1 - A status property classifier of social media user's personality for customer-oriented intelligent marketing systems
T2 - Intelligent-based marketing activities
AU - Chen, Tsung Yi
AU - Chen, Yuh Min
AU - Tsai, Meng Che
N1 - Publisher Copyright:
Copyright © 2020, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. behaviors (Knapp & Daly, 2002). The relationship between psychological characteristics, also known as personality traits, and communication strategies is that personality dominates interactive behaviors and communication methods between individuals, indicating that individuals with different personality traits tend to use different approaches to communicate. Therefore, if enterprises want to implement more precise adaptive selling activities for customers, customers' personality information will serve as a highly valued reference.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85076636745
UR - https://www.scopus.com/pages/publications/85076636745#tab=citedBy
U2 - 10.4018/IJSWIS.2020010102
DO - 10.4018/IJSWIS.2020010102
M3 - Article
AN - SCOPUS:85076636745
SN - 1552-6283
VL - 16
SP - 25
EP - 46
JO - International Journal on Semantic Web and Information Systems
JF - International Journal on Semantic Web and Information Systems
IS - 1
ER -