Spatio-temporal Signal Recovery from Political Tweets in Indonesia

Social Computing(2013)

引用 4|浏览0
暂无评分
摘要
Online social network community now provides an enormous volume of data for analyzing human sentiment about people, places, events and political activities. It is becoming increasingly clear that analysis of such data can provide great insights on the social, political and cultural aspects of the participants of these networks. As part of the Minerva project, currently underway at Arizona State University, we have analyzed a large volume of Twitter data to understand radical political activity in the provinces of Indonesia. Based on analysis of radical/counter radical sentiments expressed in tweets by Twitter users, we create a Heat Map of Indonesia which visually demonstrates the degree of radical activities in various provinces of Indonesia. We create the Heat Map of Indonesia by computing (i) the Radicalization Index and (ii) the Location Index of each Twitter user from Indonesia, who has expressed some radical sentiment in her tweets. The conclusions derived from our analysis matches significantly with the analysis of Wahid Institute, a leading political think tank of Indonesia, thus validating our results.
更多
查看译文
关键词
radicalization index,heat map,radical political activity,twitter user,location index,radical sentiment,twitter data,political tweets,radical activity,spatio-temporal signal recovery,political activity,online social network community,politics,information analysis
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要