Social media for crisis management: clustering approaches for sub-event detection

This data was imported from Scopus:

Authors: Pohl, D., Bouchachia, A. and Hellwagner, H.

http://eprints.bournemouth.ac.uk/22869/

Journal: Multimedia Tools and Applications

Volume: 74

Issue: 11

Pages: 3901-3932

eISSN: 1573-7721

ISSN: 1380-7501

DOI: 10.1007/s11042-013-1804-2

© 2013, Springer Science+Business Media New York. Social media is getting increasingly important for crisis management, as it enables the public to provide information in different forms: text, image and video which can be valuable for crisis management. Such information is usually spatial and time-oriented, useful for understanding the emergency needs, performing decision making and supporting learning/training after the emergency. Due to the huge amount of data gathered during a crisis, automatic processing of the data is needed to support crisis management. One way of automating the process is to uncover sub-events (i.e., special hotspots) in the data collected from social media to enable better understanding of the crisis. We propose in the present paper clustering approaches for sub-event detection that operate on Flickr and YouTube data since multimedia data is of particular importance to understand the situation. Different clustering algorithms are assessed using the textual annotations (i.e., title, tags and description) and additional metadata information, like time and location. The empirical study shows in particular that social multimedia combined with clustering in the context of crisis management is worth using for detecting sub-events. It serves to integrate social media into crisis management without cumbersome manual monitoring.

This data was imported from Scopus:

Authors: Pohl, D., Hellwagner, H. and Bouchachia, A.

http://eprints.bournemouth.ac.uk/22869/

Journal: Multimedia Tools and Applications

Pages: 1-32

eISSN: 1573-7721

ISSN: 1380-7501

DOI: 10.1007/s11042-013-1804-2

Social media is getting increasingly important for crisis management, as it enables the public to provide information in different forms: text, image and video which can be valuable for crisis management. Such information is usually spatial and time-oriented, useful for understanding the emergency needs, performing decision making and supporting learning/training after the emergency. Due to the huge amount of data gathered during a crisis, automatic processing of the data is needed to support crisis management. One way of automating the process is to uncover sub-events (i.e., special hotspots) in the data collected from social media to enable better understanding of the crisis. We propose in the present paper clustering approaches for sub-event detection that operate on Flickr and YouTube data since multimedia data is of particular importance to understand the situation. Different clustering algorithms are assessed using the textual annotations (i.e., title, tags and description) and additional metadata information, like time and location. The empirical study shows in particular that social multimedia combined with clustering in the context of crisis management is worth using for detecting sub-events. It serves to integrate social media into crisis management without cumbersome manual monitoring. © 2013 Springer Science+Business Media New York.

This source preferred by Hamid Bouchachia

This data was imported from Web of Science (Lite):

Authors: Pohl, D., Bouchachia, A. and Hellwagner, H.

http://eprints.bournemouth.ac.uk/22869/

Journal: MULTIMEDIA TOOLS AND APPLICATIONS

Volume: 74

Issue: 11

Pages: 3901-3932

eISSN: 1573-7721

ISSN: 1380-7501

DOI: 10.1007/s11042-013-1804-2

The data on this page was last updated at 04:42 on September 24, 2017.