Identification and classification of extremist-related tweets is a hot issue. Extremist gangs have been involved in using social media sites like Facebook and Twitter for propagating their ideology and recruitment of individuals. This work aims at proposing a terrorism-related content analysis framework with the focus on classifying tweets into extremist and non-extremist classes. Based on user-generated social media posts on Twitter, we develop a tweet classification system using deep learning-based sentiment analysis techniques to classify the tweets as extremist or non-extremist. The experimental results are encouraging and provide a gateway for future researchers.

中文翻译：

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使用情感分析技术检测和分类基于社交媒体的极端主义从属关系

与极端主义相关的推文的识别和分类是一个热门问题。极端主义帮派已经参与使用诸如Facebook和Twitter之类的社交媒体网站来传播其意识形态和招募个人。这项工作旨在提出一个与恐怖主义有关的内容分析框架，重点是将推文分为极端主义和非极端主义两类。基于Twitter上用户生成的社交媒体帖子，我们使用基于深度学习的情绪分析技术开发了一个推文分类系统，以将这些推文归类为极端主义者或非极端主义者。实验结果令人鼓舞，并为将来的研究人员提供了门户。