一种用于tweet分类的短消息分类算法

P. Selvaperumal, A. Suruliandi
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引用次数: 14

摘要

推特用户以短信的形式发布他们的观点。Twitter主题分类是将tweet分类到一组预定义的类中。本文提出了一种新的推文分类方法,该方法利用推文、转发推文和有影响力用户推文中的URL等推文特征。在广泛的推文数据集上进行了实验。将本文算法与SVM、Naïve贝叶斯、KNN等文本分类算法在推文分类中的性能进行了比较。结果表明,该方法在推文分类方面优于传统的文本分类算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A short message classification algorithm for tweet classification
Twitter users tweet their views in the form of short text messages. Twitter topic classification is classifying the tweets in to a set of predefined classes. In this work, a new tweet classification Method that makes use of tweet features like URL's in the tweet, retweeted tweets and influential users tweet is proposed. Experiments were carried out with extensive tweet data set. The performance of the proposed algorithm in classifying the tweets was compared with the text classification algorithms like SVM, Naïve Bayes, KNN etc. It is observed that the proposed method outclasses the conventional text classification algorithms in classifying the tweets.
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