학술논문
Detecting and summarizing emergent events in microblogs and social media streams by dynamic centralities
Document Type
Conference
Source
2017 IEEE International Conference on Big Data (Big Data) Big Data (Big Data), 2017 IEEE International Conference on. :1627-1634 Dec, 2017
Subject
Language
Abstract
Methods for detecting and summarizing emergent keywords have been extensively studied since social media and microblogging activities have started to play an important role in data analysis and decision making. We present a fast system for monitoring emergent keywords and summarizing a document stream based on the dynamic semantic graphs of streaming documents. We introduce the notion of dynamic eigenvector centrality for ranking emergent keywords, and present an algorithm for summarizing emergent events that is based on the minimum weight set cover. Our system is demonstrated on the streaming Twitter data related to public security.