Personality classification based on Twitter text using Naive Bayes, KNN and SVM

Bayu Yudha Pratama, R. Sarno
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引用次数: 192

Abstract

Personality is a fundamental basis of human behavior. Personality affects the interaction and preferences of an individual. People are required to take a personality test to find out their personality. Social media is a place where users express themselves to the world. Posts made by users of social media can be analyzed to obtain their personal information. This experiment uses text classification to predict personality based on text written by Twitter users. The languages used are English and Indonesian. Classification methods implemented are Naive Bayes, K-Nearest Neighbors and Support Vector Machine. Testing results showed Naive Bayes slightly outperformed the other methods.
基于朴素贝叶斯、KNN和支持向量机的Twitter文本个性分类
人格是人类行为的基本基础。个性影响着个体的互动和偏好。人们被要求进行性格测试以了解他们的性格。社交媒体是用户向世界表达自己的地方。通过分析用户在社交媒体上发布的帖子,可以获取用户的个人信息。这个实验使用文本分类来预测Twitter用户写的文本的性格。使用的语言是英语和印尼语。实现的分类方法有朴素贝叶斯、k近邻和支持向量机。测试结果表明,朴素贝叶斯略优于其他方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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