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Social Network Analysis and Mining
Published in: Social Network Analysis and Mining 1/2015

01-12-2015 | Original Article

Concept-based event identification from social streams using evolving social graph sequences

Authors: Yi-Shin Chen, Yi-Cheng Peng, Jheng-He Liang, Elvis Saravia, Fernando Calderon, Chung-Hao Chang, Ya-Ting Chuang, Tzu-Lung Chen, Elizabeth Kwan

Published in: Social Network Analysis and Mining | Issue 1/2015

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Abstract

Social networks, which have become extremely popular in the twenty first century, contain a tremendous amount of user-generated content about real-world events. This user-generated content relays real-world events as they happen, and sometimes even ahead of the newswire. The goal of this work is to identify events from social streams. The proposed model utilizes sliding window-based statistical techniques to extract event candidates from social streams. Subsequently, the “Concept-based evolving graph sequences” approach is employed to verify information propagation trends of event candidates and to identify those events. The experimental results show the usefulness of our approach in identifying real-world events in social streams.
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Metadata
Title
Concept-based event identification from social streams using evolving social graph sequences
Authors
Yi-Shin Chen
Yi-Cheng Peng
Jheng-He Liang
Elvis Saravia
Fernando Calderon
Chung-Hao Chang
Ya-Ting Chuang
Tzu-Lung Chen
Elizabeth Kwan
Publication date
01-12-2015
Publisher
Springer Vienna
Published in
Social Network Analysis and Mining / Issue 1/2015
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-015-0269-x

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