摘要：

以新浪微博中的用户为研究对象,分析并提取机器用户的特征,提出一种新的微博机器用户检测方法。通过层次分析法构建分类指标体系,对各指标特征进行量化评估,利用支持向量机(SVM)算法构建机器用户检测模型。测试SVM中不同核函数对各分类指标的重要性预测,并与量化评估结果进行比对,同时测试不同核函数模型的分类精度,对比两项结果综合选择出最优分类器。实验结果表明,该方法能够对微博中的机器用户进行较为精确的检测。

关键词: 机器用户检测, 特征提取, 量化评估, 层析分析法, 支持向量机, 最优分类器

Abstract:

Taking sina Microblog bot users as the object of study,this paper analyses and extracts features of the bot user and proposes a new Microblog bot user identification method.Through the Analytic Hierarchy Process(AHP),it constructs an index system and makes quantitative evaluation of each index feature.It uses Support Vector Machine(SVM) to construct a bot-user identification model.It tests different kernel functions that the importance prediction of each classification index,compared with the result of quantitative evaluation.Meanwhile,using different kernel functions tests the classification accuracy.According to the two results,the optimal classifier is selected.Experimental result shows that the identification method can make an accurate detection to the bot user.

Key words: bot-user identification, feature extraction, quantitative evaluation, Analytic Hierarchy Process(AHP), Support Vector Machine(SVM), optimal classifier

中图分类号: 

• TP391