ABSTRACT

Online social media such as Twitter are growing so rapidly. Recently, Twitter has become one of the popular microblogging services on the Internet. It lets millions of users to communicate and interact by sending short messages of up to 140 characters. The massive amount of information over the web from Twitter requires an automatic tool that can determine the topics that people are talking about. The Topic Detection task is concentrated on discovering the main topics automatically. In this article at first, we explore different approaches to detect topics of tweets. Then, we will classify these topic detection approaches to four classes of categories, including with word embedding or without word embedding, specified or unspecified, offline (RED) or online (NED), and supervised or unsupervised. Finally, we will discuss the studied approaches in detail.

摘要

Twitter 等在线社交媒体发展迅速。最近，Twitter 已成为互联网上流行的微博服务之一。它允许数百万用户通过发送最多 140 个字符的短消息进行交流和互动。来自 Twitter 的网络上的大量信息需要一个自动工具来确定人们正在谈论的话题。主题检测任务专注于自动发现主要主题。在本文中，我们首先探索检测推文主题的不同方法。然后，我们将这些主题检测方法分为四类，包括有词嵌入或无词嵌入、指定或未指定、离线 (RED) 或在线 (NED) 以及有监督或无监督。最后，