Identifying and Tracking Sentiments and Topics from Social Media Texts during Natural Disasters
来源:互联网 发布:汽车防盗编程器 编辑:程序博客网 时间:2024/06/06 00:25
作者提供了数据和代码(不是很多):https://goo.gl/uee3QK
按照惯例,不解释技术细节,只介绍文章的问题和方法,先看图:
location-based dynamic sentiment-topic model (LDST)——考虑了地点,情感和话题的动态模型(动态主要提现在地点的变化,引起的情感和话题的变化)
论文假设存在作者,地点和文档集合,对于特定时间戳,利用V和U表示地点和用户,文档d作为短文本被用户u在地点v,时间t发布。同时S是情感标签,T是话题个数。
Since each tweet is a short text, studying them individually is not very informative.
这里作者集合文档,根据地点或者作者。
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