信息网络安全 ›› 2016, Vol. 16 ›› Issue (9): 234-239.doi: 10.3969/j.issn.1671-1122.2016.09.046

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面向Twitter的分析系统研究

温俊伟()   

  1. 中国人民公安大学,北京 102623
  • 收稿日期:2016-07-25 出版日期:2016-09-20 发布日期:2020-05-13
  • 作者简介:

    作者简介: 温俊伟(1993—),男,福建,本科,主要研究方向为网络安全研究。

Research on Twitter Oriented Analysis System

Junwei WEN()   

  1. People's Public Security University of China, Beijing 102623, China
  • Received:2016-07-25 Online:2016-09-20 Published:2020-05-13

摘要:

随着许多像Twitter一样具有全球影响力的社交网站的出现,舆论的影响力也开始跨越不同国家之间的界限,网络监察部门开始需要关注与评估国外舆论对国内的影响,而Twitter必然成为一个关注的焦点。文章基于社交媒体数据挖掘的关键技术和网络分析的相关理论,运用Python、graph-tool和NLTK等相关工具包,设计并实现了一个对Twitter进行数据搜集存储、数据分析和分析结果交互展示的综合分析系统。该系统能实时地搜集并展示某一地区的热门话题及相关推特文章,可以对推文进行情感分析展示;能够获取指定用户指定大小的个人关系网络,利用接近中心性、介数中心性以及Pagerank算法对该网络进行个体影响力分析,使用随机块模型对该网络进行社区发现。系统测试符合预期,为公安网络舆情监察工作提供了一定的参考与帮助。

关键词: Twitter, 情感分析, 网络个体影响力, 社区发现, 分析系统

Abstract:

With the emergence of a large number of globally influential social networking sites like Twitter, the influence of public opinion crosses over the boundary of nation. Network monitoring department began to pay attention to and assess the impact of foreign public opinion on the domestic environment, and Twitter is bound to be a focus of attention. This paper, based on the theory of social media data mining and network analysis, designs and implements a Twitter oriented comprehensive analysis system for data collection and storage, data analysis and interactive display of analysis results with Python, graph-tool, NLTK and other related tools. The system can collect and display the hot topics and related tweets in a certain area in real time, doing sentiment analysis of tweets. At the same time, system can get the relationship network of specified user and specified size, using theory of Closeness Centrality, Betweeness Centrality and PageRank algorithm for individual influence analysis and building Stochastic Block Model for community structure discovery in Networks. System testing is in line with expectations and I hope this system could provide reference and help for the public security work of public opinion on the internet.

Key words: Twitter, sentiment analysis, network individual influence, community discovery, analysis system

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