A Method for Extracting Task-Related Information from Social Media Based On Structured Domain Knowledge

Link, D., De Albuquerque, J. P. , Horita, F. E. A., Hellingrath, B. and Ghasemivandhonaryar, S. (2015) A Method for Extracting Task-Related Information from Social Media Based On Structured Domain Knowledge. In: 21st Americas Conference on Information Systems (AMCIS 2015), Fajardo, Puerto Rico, 13-15 Aug 2015, ISBN 9780996683104

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Abstract

Social media platforms have come into the focus of research as sources of information about the unfolding situation in disaster contexts. Incorporating information from social media into decision-making is still difficult though. One reason may be that the prevalent approach to data analysis works bottom-up, which has several limitations. In this paper, we adopt a top-down approach by means of a novel keyword-based method for identifying potentially relevant information in social media data based on structured knowledge of activities undertaken in a domain. The application of the method to the context of humanitarian logistics using four social media datasets shows its capability to identify potentially relevant information via reference tasks and to match identified information with decision-makers' activities. In addition, we offer a first set of domain-specific keywords to identify information related to infrastructure and resources in humanitarian logistics.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Porto de Albuquerque, Professor Joao
Authors: Link, D., De Albuquerque, J. P., Horita, F. E. A., Hellingrath, B., and Ghasemivandhonaryar, S.
College/School:College of Social Sciences > School of Social and Political Sciences > Urban Studies
Journal Name:2015 Americas Conference on Information Systems, AMCIS 2015
ISBN:9780996683104
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