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

Lingfei Zhang, Chunfang Li
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引用次数: 1

Abstract

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.
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基于LDA和情感分析的Twitter新闻报道热点挖掘方法研究
如今,各国媒体就国际热点话题发布了大量的报道推文。新闻事件在推特上的快速传播越来越受欢迎。对于新闻事件的热点挖掘,话题划分和情感分析是不可或缺的两个因素。本文采用话题分割和情感分析的方法,对2019年美国媒体和中国媒体在华为相关新闻中的推文进行社交媒体新闻热点挖掘。首先,我们利用LDA对媒体推文进行主题划分,得到相关主题词。然后,我们设计了改进的方法,分别对媒体推文和网红评论进行有效的情感分析。此外,我们还得出了一些关于社交媒体推文新闻热点挖掘的有效结论。
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Behavioral Decision Makings: Reconciling Behavioral Economics and Decision Systems Operating System Classification: A Minimalist Approach Research on Hotspot Mining Method of Twitter News Report Based on LDA and Sentiment Analysis Conservative Generalisation for Small Data Analytics –An Extended Lattice Machine Approach ICMLC 2020 Cover Page
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