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首页> 外文期刊>International journal of information retrieval research >Twitter Users' Classification Based on Interest: Case Study on Arabic Tweets
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Twitter Users' Classification Based on Interest: Case Study on Arabic Tweets

机译：基于兴趣的Twitter用户分类：阿拉伯文推文案例研究

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摘要

Microblogging platforms, such as Twitter, have become a popular interaction media that are used widely for different daily purposes, such as communication and knowledge sharing. Understanding the behaviors and interests of these platforms' users become a challenge that can help in different areas such as recommendation and filtering. In this article, an approach is proposed for classifying Twitter users with respect to their interests based on their Arabic tweets. A Multinomial Naive Bayes machine learning algorithm is used for such classification. The proposed approach has been developed as a web-based software system that is integrated with Twitter using Twitter API. An experimental study on Arabic tweets has been investigated on the proposed system as a case study.
机译：微博平台（例如Twitter）已成为一种流行的交互媒体，已广泛用于各种日常用途，例如通信和知识共享。了解这些平台用户的行为和兴趣成为一项挑战，可以在不同领域提供帮助，例如推荐和过滤。在本文中，提出了一种基于阿拉伯语推文对Twitter用户按照其兴趣进行分类的方法。多项朴素贝叶斯机器学习算法用于这种分类。提议的方法已开发为基于Web的软件系统，并使用Twitter API与Twitter集成。已对拟议系统上的阿拉伯文推文进行了实验研究，作为案例研究。

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