Meme Extraction and Tracing in Crisis Events

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 互联网大数据与安全信息学研究中心

	Meme Extraction and Tracing in Crisis Events
	Saike He; Xiaolong Zheng; Jiaojiao Wang; Zhijun Chang ; Yin Luo ; Daniel Zeng
	2016-10
会议名称	the 2016 IEEE International Conference on Intelligence and Security Informatics
会议日期	September 28-30, 2016
会议地点	Tucson, Arizona USA
关键词	meme extraction meme tracing accessor variety
通讯作者	Xiaolong Zheng, Jiaojiao Wang
英文摘要	The proliferation of social media has increased the competition among different memes, which can be free texts, trending catchphrases, or micro media. As human attention is limited, these memes compete with each other, and go in and out of popularity at a rapid pace, sometimes even faster than we can recognize. Popular memes often shape the mindsets of online communities, and also shed light on their future tendencies. Considering the huge volume of memes generated and their continuous mutations, extracting and tracing online memes automatically is rather challenging. In this paper, we propose an automatic meme extraction algorithm. The proposed algorithm extracts massive memes based on phrases independency, and clusters phrase variants of a single meme efficiently. Evaluation on measles outbreak in the USA in 2015 indicates that the proposed algorithm could extract typical memes reflecting the fierce campaign between the pro-vaccination community and the anti-vaccination community. In both communities, memes are power-law distributed, and popular ones have many variants that appear more frequently. By tracing the evolution of online memes, we uncover that popular memes converge and generate peaks at times. Though the pro-vaccination community and the anti-vaccination community may focus on similar memes, they comprehend memes from totally different perspectives and deliver opposing opinions of measles vaccination.
会议录	Proceedings paper of IEEE International Conference on Intelligence and Security Informatics: Cybersecurity and Big Data
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/12092]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心
作者单位	1.The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences 2.School of Management and Economics, Beijing Institute of Technology 3.University of Chinese Academy of Sciences, Beijing, China
推荐引用方式 GB/T 7714	Saike He,Xiaolong Zheng,Jiaojiao Wang,et al. Meme Extraction and Tracing in Crisis Events[C]. 见:the 2016 IEEE International Conference on Intelligence and Security Informatics. Tucson, Arizona USA. September 28-30, 2016.