基于词共现模型的微博热点话题检测

Long Cao, Xin Chen, Yuqing Zhang, Donghui Li
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引用次数: 0

摘要

微博服务被世界各地数以百万计的人用来获取信息和表达意见。从中国的微博中发现热点话题对于发现谣言和引导舆论有着巨大的重要性。为了解决微博平台信息量大的问题和微博内容文本短的特点,本文提出了一种基于词共现模型的中文微博热点话题检测模型。实验结果表明,该模型能够有效地检测中文微博中的热点话题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hot topics detected from micro-bloggings based on word co-occurrence model
Micro-blogging services are used by millions of people around the world to get information and express their opinions. Detecting hot topics from Chinese micro-bloggings has vast importance to discovering rumors and guiding public opinion. In order to solve the problem of massive pieces of information on micro-bloggings platform and the feature of micro-bloggins content such as short text, in this paper a model is put forward to detect hot topics from Chinese micro-bloggings based on word co-occurrence model. The experimental results show the model can efficiently detect hot topics from Chinese micro-bloggings.
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