IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v20y2018i5d10.1007_s10796-016-9712-4.html
   My bibliography  Save this article

Multimode co-clustering for analyzing terrorist networks

Author

Listed:
  • Ahmed Aleroud

    (Yarmouk University)

  • Aryya Gangopadhyay

    (University of Maryland, Baltimore County (UMBC))

Abstract

The phenomenon of terrorism is deemed one of the fundamental challenges in national security. Creating defensive technologies to mitigate terrorist attacks requires a simultaneous investigation of contextual relationships among their various dimensions. We proposed and evaluated a graph-based methodology to analyze terrorist networks through co-clustering in a multimode basis. Since there are many heterogeneous relationships in terrorist networks depending on the dimensions used during analysis, we utilized the clustering indicators of the multimode structure discovered in bi- and multimode graphs. Objects and activities that co-occur during terrorist attacks are identified by applying conventional clustering on those indicators. The novelty of our method is in the incremental creation of the multimode structure using its bi-mode counterparts. Our approach is evaluated using these measures: clustering stability and association confidence. The experimental results yields encouraging results in terms of simultaneous clustering of heterogeneous objects in terrorist networks.

Suggested Citation

  • Ahmed Aleroud & Aryya Gangopadhyay, 2018. "Multimode co-clustering for analyzing terrorist networks," Information Systems Frontiers, Springer, vol. 20(5), pages 1053-1074, October.
    • Handle: RePEc:spr:infosf:v:20:y:2018:i:5:d:10.1007_s10796-016-9712-4
    DOI: 10.1007/s10796-016-9712-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-016-9712-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-016-9712-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Marc Cheong & Vincent C. S. Lee, 2011. "A microblogging-based approach to terrorism informatics: Exploration and chronicling civilian sentiment and response to terrorism events via Twitter," Information Systems Frontiers, Springer, vol. 13(1), pages 45-59, March.
    2. Onook Oh & Manish Agrawal & H. Raghav Rao, 2011. "Information control and terrorism: Tracking the Mumbai terrorist attack through twitter," Information Systems Frontiers, Springer, vol. 13(1), pages 33-43, March.
    3. Jiexun Li & G. Alan Wang & Hsinchun Chen, 2011. "Identity matching using personal and social identity features," Information Systems Frontiers, Springer, vol. 13(1), pages 101-113, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Raj Bridgelall, 2022. "Applying unsupervised machine learning to counterterrorism," Journal of Computational Social Science, Springer, vol. 5(2), pages 1099-1128, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hsinchun Chen & Yilu Zhou & Edna F. Reid & Catherine A. Larson, 2011. "Introduction to special issue on terrorism informatics," Information Systems Frontiers, Springer, vol. 13(1), pages 1-3, March.
    2. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.
    3. Jengchung Victor Chen & I-Han Lu & David C. Yen & Andree E. Widjaja, 2017. "Factors affecting the performance of internal control task team in high-tech firms," Information Systems Frontiers, Springer, vol. 19(4), pages 787-802, August.
    4. Yanxin Wang & Jian Li & Xi Zhao & Gengzhong Feng & Xin (Robert) Luo, 2020. "Using Mobile Phone Data for Emergency Management: a Systematic Literature Review," Information Systems Frontiers, Springer, vol. 22(6), pages 1539-1559, December.
    5. Fang Liu & Dongming Xu, 2018. "Social Roles and Consequences in Using Social Media in Disasters: a Structurational Perspective," Information Systems Frontiers, Springer, vol. 20(4), pages 693-711, August.
    6. Ahmed Aleroud & Aryya Gangopadhyay, 0. "Multimode co-clustering for analyzing terrorist networks," Information Systems Frontiers, Springer, vol. 0, pages 1-22.
    7. Shabir Hussain & Farrukh Shahzad & Adam Saud, 2021. "Analyzing the State of Digital Information Warfare Between India and Pakistan on Twittersphere," SAGE Open, , vol. 11(3), pages 21582440211, July.
    8. Bairong Wang & Jun Zhuang, 2018. "Rumor response, debunking response, and decision makings of misinformed Twitter users during disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(3), pages 1145-1162, September.
    9. Avinash Samuel & Dilip Kumar Sharma, 2018. "A Novel Framework for Sentiment and Emoticon-Based Clustering and Indexing of Tweets," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-18, June.
    10. Reimer, Thomas, 2023. "Environmental factors to maximize social media engagement: A comprehensive framework," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    11. Li, Lifang & Zhang, Qingpeng & Tian, Jun & Wang, Haolin, 2018. "Characterizing information propagation patterns in emergencies: A case study with Yiliang Earthquake," International Journal of Information Management, Elsevier, vol. 38(1), pages 34-41.
    12. M. Elshendy & A. Fronzetti Colladon & E. Battistoni & P. A. Gloor, 2021. "Using four different online media sources to forecast the crude oil price," Papers 2105.09154, arXiv.org.
    13. Yogesh K. Dwivedi & Gerald Kelly & Marijn Janssen & Nripendra P. Rana & Emma L. Slade & Marc Clement, 2018. "Social Media: The Good, the Bad, and the Ugly," Information Systems Frontiers, Springer, vol. 20(3), pages 419-423, June.
    14. Fry, John & Binner, Jane M., 2016. "Elementary modelling and behavioural analysis for emergency evacuations using social media," European Journal of Operational Research, Elsevier, vol. 249(3), pages 1014-1023.
    15. Irina Wedel & Michael Palk & Stefan Voß, 2022. "A Bilingual Comparison of Sentiment and Topics for a Product Event on Twitter," Information Systems Frontiers, Springer, vol. 24(5), pages 1635-1646, October.
    16. Ruochen Liao & Shenaz Balasinorwala & H. Raghav Rao, 2017. "Computer assisted frauds: An examination of offender and offense characteristics in relation to arrests," Information Systems Frontiers, Springer, vol. 19(3), pages 443-455, June.
    17. Zhan, Yuanzhu & Xiong, Yu & Xing, Xinjie, 2023. "A conceptual model and case study of blockchain-enabled social media platform," Technovation, Elsevier, vol. 119(C).
    18. Stefan Stieglitz & Christian Meske & Björn Ross & Milad Mirbabaie, 2020. "Going Back in Time to Predict the Future - The Complex Role of the Data Collection Period in Social Media Analytics," Information Systems Frontiers, Springer, vol. 22(2), pages 395-409, April.
    19. Jengchung Victor Chen & I-Han Lu & David C. Yen & Andree E. Widjaja, 0. "Factors affecting the performance of internal control task team in high-tech firms," Information Systems Frontiers, Springer, vol. 0, pages 1-16.
    20. Agarwal, Puneet & Aziz, Ridwan Al & Zhuang, Jun, 2022. "Interplay of rumor propagation and clarification on social media during crisis events - A game-theoretic approach," European Journal of Operational Research, Elsevier, vol. 298(2), pages 714-733.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:infosf:v:20:y:2018:i:5:d:10.1007_s10796-016-9712-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.