你的一举一动我都会盯着你:推特上的地理焦点检测

F. Peregrino, D. Tomás, F. Llopis
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引用次数: 8

摘要

在线社交网络自创建以来迅速普及,提供了大量的数据,可以利用这些数据提取与商业和社会人类行为相关的有用信息。可以提取的最有用的信息之一是地理信息。本文展示了一种基于用户发送的tweet文本和来自维基百科的外部信息来检测城市级别Twitter用户地理焦点的方法。这项工作的主要目标是展示外部正式文本资源(如维基百科)在解决非正式自然语言文本短片段中的地理焦点时的重要性。为了实现这一目标,我们用语言模型系统评估了我们的系统,只使用非正式的文本片段(tweet)比较结果,并将其与来自维基百科的正式文本合并。在我们的实验中,我们发现,当现有的数据量相当有限时,从维基百科文章和链接中获得的正式文本片段的帮助可能会很有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Every move you make I'll be watching you: geographical focus detection on Twitter
On-line Social Networks have increased their popularity rapidly since their creation, providing a huge amount of data which can be leverage to extract useful information related to commercial and social human behaviours. One of the most useful information that can be extracted is the geographical one. This paper shows an approach to detect the geographical focus of Twitter users at city level based on the text of the tweets that users have sent and external information from Wikipedia. The main goal of this work is to show how important could be external formal text resources such as Wikipedia when it comes to resolve the geographical focus in short pieces of informal natural language text. In order to accomplish this objective, we have assessed our system with a language model system, comparing the results using only the informal pieces of text (tweets) and merging it with formal text coming from Wikipedia. In our experiments, we found that the aid of formal pieces of text, such as those obtained from the Wikipedia articles and links, could be useful when the existing amount of data is rather limited.
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