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Author (up) Asmelash Teka Hadgu; Sallam Abualhaija; Claudia Niederée
Title Real-time Adaptive Crawler for Tracking Unfolding Events on Twitter Type Conference Article
Year 2019 Publication Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2019
Volume Issue Pages
Keywords social search, real-time adaptive search, event tracking, crsis communication
Abstract When a major event such as a crisis situation occurs, people post messages on social media sites such as Twitter, in

order to exchange information or to share emotions. These posts can provide useful information to raise situation

awareness and support decision making, e.g., by aid organizations. In this paper, we propose a novel method for

social media crawling, which exploits a Bayesian inference framework to keep track of keyword changes over time

and uses a counter-stream to gauge the inclusion of noise and irrelevant information. In addition, we present a

framework to evaluate real-time adaptive social search algorithms in a reproducible manner, which relies on a

semi-automated approach for ground-truth construction. We show that our method outperforms previous methods

for very large scale events.
Address L3S Research Center, Leibniz universität Hannover, Germany;Interdisciplinary Centre for Security, Reliability and Trust
Corporate Author Thesis
Publisher Iscram Place of Publication Valencia, Spain Editor Franco, Z.; González, J.J.; Canós, J.H.
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 978-84-09-10498-7 Medium
Track T8- Social Media in Crises and Conflicts Expedition Conference 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019)
Notes Approved no
Call Number Serial 1985
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