首页> 外文期刊>Procedia Computer Science >Personality Classification of Facebook Users According to Big Five Personality Using SVM (Support Vector Machine) Method
【24h】

Personality Classification of Facebook Users According to Big Five Personality Using SVM (Support Vector Machine) Method

机译:使用SVM(支持向量机)方法的大五个个性的Facebook用户的个性分类

获取原文
       

摘要

Social media has become one of the most important things in daily life to communicate, show expression and exchange information. Facebook is one of the most widely used social media. This research focuses on classifying the personality of Facebook users into one of the Big Five Personality Traits. there are 170 volunteers who are Facebook users who have been asked to fill out the Big Five Inventory questionnaire and have allowed their data to be scraped. Based on the data collected, the classifier is built using data mining techniques using Support Vector Machine (SVM) that aim to find out someone’s personality based on a Facebook account without having to fill in any questionnaire. The best accuracy results in this study with a classification model that has been built at 87.5% using the Radial Basis Function (RBF) kernel.
机译:社交媒体已成为日常生活中最重要的事情之一,以沟通,展示表达和交换信息。 Facebook是最广泛使用的社交媒体之一。这项研究侧重于将Facebook用户的个性分类为庞大的五种人格特质之一。有170名志愿者是Facebook用户被要求填写五大库存问卷,并允许他们的数据刮擦。基于收集的数据,分类器采用数据挖掘技术使用支持向量机(SVM)构建,该技术旨在根据Facebook帐户找到某人的个性,而无需填写任何调查表。本研究中的最佳准确性结果与径向基函数(RBF)内核以87.5%建立在87.5%的分类模型。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号