Online indexing and clustering of social media data for emergency management

Article English OPEN
Pohl, D. ; Bouchachia, Abdelhamid ; Hellwagner, H. (2015)

Social media becomes a vital part in our daily communication practice, creating a huge amount of data and covering different real-world situations. Currently, there is a tendency in making use of social media during emergency management and response. Most of this effort is performed by a huge number of volunteers browsing through social media data and preparing maps that can be used by professional first responders. Automatic analysis approaches are needed to directly support the response teams in monitoring and also understanding the evolution of facts in social media during an emergency situation. In this paper, we investigate the problem of real-time sub-events identification in social media data (i.e., Twitter, Flickr and YouTube) during emergencies. A processing framework is presented serving to generate situational reports/summaries from social media data. This framework relies in particular on online indexing and online clustering of media data streams. Online indexing aims at tracking the relevant vocabulary to capture the evolution of sub-events over time. Online clustering, on the other hand, is used to detect and update the set of sub-events using the indices built during online indexing. To evaluate the framework, social media data related to Hurricane Sandy 2012 was collected and used in a series of experiments. In particular some online indexing methods have been tested against a proposed method to show their suitability. Moreover, the quality of online clustering has been studied using standard clustering indices. Overall the framework provides a great opportunity for supporting emergency responders as demonstrated in real-world emergency exercises.
  • References (65)
    65 references, page 1 of 7

    [1] L. Palen, Online social media in crisis events, EDUCAUSE Q. (EQ) 31 (3) (2008) 76-78 〈http://www.educause.edu/〉.

    [2] S. Vieweg, A.L. Hughes, K. Starbird, L. Palen, Microblogging during two natural hazards events: what twitter may contribute to situational awareness, in: Proceedings of the 28th International Conference on Human Factors in Computing Systems, CHI '10, ACM, New York, NY, USA, 2010, pp. 1079-1088.

    [3] R. Westbrook, T. Karlgaard, C. White, J. Knapic, A holistic approach to evaluating social media's successful implementation into emergency management operations: applied research in an action research study, Int. J. Inf. Syst. Crisis Response Manag. 4 (2012) 1-13.

    [4] D. Pohl, A. Bouchachia, H. Hellwagner, Automatic sub-event detection in emergency management using social media, in: First International Workshop on Social Web for Disaster Management (SWDM), in conjunction with WWW'12, ACM, Lyon, France, 2012, pp. 683-686.

    [5] D. Pohl, A. Bouchachia, H. Hellwagner, Online processing of social media data for emergency management, in: International Conference on Machine Learning and Applications (ICMLA), vol. 2, 2013, pp. 333-338. doi:http://dx.doi.org/ 10.1109/ICMLA.2012.170.

    [6] A. Bouchachia, C. Vanaret, GT2FC: an online growing interval type-2 selflearning fuzzy classifier, IEEE Trans. Fuzzy Syst. 22 (4) (2014) 999-1018.

    [7] M. Gao, V.K. Singh, R. Jain, Eventshop: from heterogeneous web streams to personalized situation detection and control, in: Proceedings of the 3rd Annual ACM Web Science Conference, WebSci '12, ACM, New York, NY, USA, 2012, pp. 105-108.

    [8] V. Lampos, N. Cristianini, Nowcasting events from the social web with statistical learning, ACM Trans. Intell. Syst. Technol. 3 (4) (2012) 72:1-72:22.

    [9] V. Lampos, N. Cristianini, Tracking the flu pandemic by monitoring the social web, in: International Workshop on Cognitive Information Processing (CIP), 2010, pp. 411-416. doi:http://dx.doi.org/10.1109/CIP.2010.5604088.

    [10] M. Krstajic, C. Rohrdantz, M. Hund, A. Weiler, Getting there first: real-time detection of real-world incidents on twitter, in: 2nd Workshop on Interactive Visual Text Analytics: Task-Driven Analysis of Social Media Content with Visweek'12, 2012, pp. 1-4.

  • Metrics
    0
    views in OpenAIRE
    0
    views in local repository
    103
    downloads in local repository

    The information is available from the following content providers:

    From Number Of Views Number Of Downloads
    Bournemouth University Research Online - IRUS-UK 0 103
Share - Bookmark