Discovering users' topics of interest on twitter: a first look
Discovering users' topics of interest on twitter: a first look
复制标题
DOI：
10.1145/1871840.1871852
复制
发表时间：
2010-10
影响因子：
5.4
通讯作者：
M. Michelson;Sofus A. Macskassy
中科院分区：
文献类型：
--
作者：
M. Michelson;Sofus A. Macskassy
微博客服务Twitter为用户提供了一个框架，让他们可以写一些简短的，经常是嘈杂的关于他们生活的帖子。这些帖子被称为“推特”。“在本文中，我们通过检查Twitter用户在推文中提到的实体来发现他们感兴趣的话题。我们的方法利用知识库来消除歧义和分类推文中的实体。然后，我们开发了一个“主题配置文件”，它通过识别哪些类别经常出现并覆盖实体来描述用户感兴趣的主题。我们证明，即使在这个早期的工作，我们能够成功地发现在我们的研究中的用户感兴趣的主要议题。
Twitter, a micro-blogging service, provides users with a framework for writing brief, often-noisy postings about their lives. These posts are called "Tweets." In this paper we present early results on discovering Twitter users' topics of interest by examining the entities they mention in their Tweets. Our approach leverages a knowledge base to disambiguate and categorize the entities in the Tweets. We then develop a "topic profile," which characterizes users' topics of interest, by discerning which categories appear frequently and cover the entities. We demonstrate that even in this early work we are able to successfully discover the main topics of interest for the users in our study.