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

机译:以客户为导向智能营销系统社交媒体用户人格的状态属性分类器:基于智能的营销活动

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摘要

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.
机译:企业需要获取有关特定客户偏好的信息,而且更重要的是,顾客的心理特征,显着影响其消费行为和对智能营销活动的反应。如果企业希望为客户实施更精确的智能销售活动,客户的个性信息将作为一个高度重视的参考。本研究中提出的自动检测方法基于文本语义挖掘和机器学习,以通过收集和分析目标的社交媒体数据来对目标进行人格类型预测的技术。在测试中,获得了5,858个状态,其中815个标记,具有122个有效标签。通常,当n = 5时,标记速率可达到60-80%。本研究中提出的状态属性分类器(SPC)可以通过在状态集上进行文本语义挖掘来预测用户发布具有高精度的状态集的人格类型(PT)。

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