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Research on Hotspot Mining Method of Twitter News Report Based on LDA and Sentiment Analysis

机译:基于LDA和情感分析的推特新闻报告热点挖掘方法研究

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Nowadays, media from various countries have published a large number of report tweets on international hot topics. The rapid spread of news events on twitter has become increasingly popular. For hotspot mining of news events, topic division and sentiment analysis are two indispensable factors. In this Paper, we use topic segmentation and sentiment analysis to conduct hot mining of social media news for the US media and Chinese media tweets in Huawei-related news in 2019. First, we apply LDA to media tweets to divide topics and obtain related topic words. Then we devised improved methods for effective sentiment analysis on media tweets and influencer comments respectively. What's more, we draw some valid conclusions about news hotspot mining in social media tweets.
机译:如今,来自各国的媒体已经发表了大量报告推文关于国际热门话题。 新闻事件在Twitter上的快速传播变得越来越受欢迎。 对于新闻事件的热点挖掘,主题分部和情绪分析是两个不可或缺的因素。 在本文中,我们使用主题细分和情感分析,在2019年在华为相关新闻中为美国媒体和中国媒体推文进行社交媒体新闻的热门挖掘。首先,我们将LDA应用于媒体推文,以除以主题并获得相关主题 字。 然后,我们分别设计了对媒体推文和影响者评论的有效情感分析的改进方法。 更重要的是,我们在社交媒体推文中汲取了关于新闻热点挖掘的有效结论。

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