Prediction of interest for dynamic profile of Twitter user

Elisafina Siswanto, M. L. Khodra, L. J. E. Dewi
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引用次数: 6

Abstract

Numerous studies have been conducted to explore the social network of Twitter; some have been conducted to predict the interest or the topic of the user's tweet. In this study, we investigate the best classification model for determining the user's interest based on the bio and a collection of tweets. We use the supervised learning-based classification with the lexical features. Two approaches were proposed; they are the classification that was made based on the user's tweet using multilabel classification method and the classification that was made based on specific accounts. From the result of experimental result, it could be concluded that the employment of the classification using specific accounts approach led to better accuracy.
对Twitter用户动态配置文件的兴趣预测
已经进行了大量的研究来探索Twitter的社交网络;有些是用来预测用户推文的兴趣或主题的。在这项研究中,我们研究了基于个人简介和tweet集合来确定用户兴趣的最佳分类模型。我们使用基于监督学习的词汇特征分类。提出了两种方法;一种是基于用户tweet使用多标签分类方法进行的分类,另一种是基于具体账号进行的分类。从实验结果可以看出,采用具体账户法分类具有更好的准确率。
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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