IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i15p9711-d882100.html
   My bibliography  Save this article

Exploring the Bedouin Syndrome in the Football Fan Culture: Addressing the Hooliganism Phenomena through Networks of Violent Behavior

Author

Listed:
  • Thyago Celso Cavalcante Nepomuceno

    (Núcleo de Tecnologia, Federal University of Pernambuco, Caruaru 55014-900, Brazil)

  • Victor Diogho Heuer de Carvalho

    (Campus do Sertão, Federal University of Alagoas, Delmiro Gouveia 57480-000, Brazil)

  • Lúcio Camara e Silva

    (Núcleo de Tecnologia, Federal University of Pernambuco, Caruaru 55014-900, Brazil)

  • Jadielson Alves de Moura

    (Departamento de Engenharia de Produção, Federal University of Pernambuco, Recife 50670-901, Brazil)

  • Ana Paula Cabral Seixas Costa

    (Departamento de Engenharia de Produção, Federal University of Pernambuco, Recife 50670-901, Brazil)

Abstract

The Bedouin syndrome represents social interactions based on four premises: a friend of my friend is my friend, a friend of my enemy is my enemy, an enemy of my friend is my enemy, and an enemy of my enemy is my friend. These extensive associations exist in many social and economic relationships, such as market competition, neighborhood relations, political behavior, student gangs, organized crime, and the violent behavior of sports spectators (hooliganism) worldwide. This work tests the Bedouin syndrome hypothesis considering the violent behavior in the football fan culture. We construct relational networks of social affinities to represent the social interactions of organized fan bases ( Torcidas organizadas ) involved in hooligan violence in Pernambuco, Brazil. Contrary to prior expectations, the results evidence no statistical support for the Bedouin syndrome in 13 of the 15 analyzed clubs. There is weak statistical support in two interactions and strong statistical support in one interaction to state that a friend of my enemy is my friend (instead of an enemy). The only support for the Bedouin syndrome is circumstantial based on a prior assumption of an alliance. We propose a network development that can be more suitable to represent football fans’ violent behavior. The results contribute to understanding the hooliganism social phenomenon in football-rooted cultures and their impact on public health, identifying potential determinants for organized violence by young spectators’ and supporting police strategies by defining relevance scores for the most potential clashes and coalitions of gangs.

Suggested Citation

  • Thyago Celso Cavalcante Nepomuceno & Victor Diogho Heuer de Carvalho & Lúcio Camara e Silva & Jadielson Alves de Moura & Ana Paula Cabral Seixas Costa, 2022. "Exploring the Bedouin Syndrome in the Football Fan Culture: Addressing the Hooliganism Phenomena through Networks of Violent Behavior," IJERPH, MDPI, vol. 19(15), pages 1-19, August.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:9711-:d:882100
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/15/9711/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/15/9711/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    2. Trevor Hale & Christopher Moberg, 2003. "Location Science Research: A Review," Annals of Operations Research, Springer, vol. 123(1), pages 21-35, October.
    3. Paul Goldsmith-Pinkham & Guido W. Imbens, 2013. "Social Networks and the Identification of Peer Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 253-264, July.
    4. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    5. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    6. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    7. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    8. Ostrom, Elinor, 1973. "On the meaning and measurement of output and efficiency in the provision of urban police services," Journal of Criminal Justice, Elsevier, vol. 1(2), pages 93-111.
    9. Leydesdorff, Loet & Rafols, Ismael, 2012. "Interactive overlays: A new method for generating global journal maps from Web-of-Science data," Journal of Informetrics, Elsevier, vol. 6(2), pages 318-332.
    10. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331.
    11. Goutam Sen & Mohan Krishnamoorthy & Narayan Rangaraj & Vishnu Narayanan, 2016. "Facility location models to locate data in information networks: a literature review," Annals of Operations Research, Springer, vol. 246(1), pages 313-348, November.
    12. Thyago C. C. Nepomuceno & Cinzia Daraio & Ana Paula C. S. Costa, 2021. "Multicriteria Ranking for the Efficient and Effective Assessment of Police Departments," Sustainability, MDPI, vol. 13(8), pages 1-15, April.
    Full references (including those not matched with items on IDEAS)

    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. Yulei Xie & Ling Ji & Beibei Zhang & Gordon Huang, 2018. "Evolution of the Scientific Literature on Input–Output Analysis: A Bibliometric Analysis of 1990–2017," Sustainability, MDPI, vol. 10(9), pages 1-17, September.
    2. Ying Huang & Wolfgang Glänzel & Lin Zhang, 2021. "Tracing the development of mapping knowledge domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6201-6224, July.
    3. Toshiyuki Hasumi & Mei-Shiu Chiu, 2022. "Online mathematics education as bio-eco-techno process: bibliometric analysis using co-authorship and bibliographic coupling," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4631-4654, August.
    4. Ci-Jyun Liang & Marvin H. Cheng, 2023. "Trends in Robotics Research in Occupational Safety and Health: A Scientometric Analysis and Review," IJERPH, MDPI, vol. 20(10), pages 1-21, May.
    5. Yue Guiling & Siti Aisyah Panatik & Mohammad Saipol Mohd Sukor & Noraini Rusbadrol & Li Cunlin, 2022. "Bibliometric Analysis of Global Research on Organizational Citizenship Behavior From 2000 to 2019," SAGE Open, , vol. 12(1), pages 21582440221, February.
    6. Loet Leydesdorff, 2013. "Statistics for the dynamic analysis of scientometric data: the evolution of the sciences in terms of trajectories and regimes," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 731-741, September.
    7. Hugo Baier-Fuentes & José M. Merigó & José Ernesto Amorós & Magaly Gaviria-Marín, 2019. "International entrepreneurship: a bibliometric overview," International Entrepreneurship and Management Journal, Springer, vol. 15(2), pages 385-429, June.
    8. Katalin Orosz & Illés J. Farkas & Péter Pollner, 2016. "Quantifying the changing role of past publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 829-853, August.
    9. Daniele Rotolo & Ismael Rafols & Michael Hopkins & Loet Leydesdorff, 2014. "Scientometric Mapping as a Strategic Intelligence Tool for the Governance of Emerging Technologies," SPRU Working Paper Series 2014-10, SPRU - Science Policy Research Unit, University of Sussex Business School.
    10. Rodolfo Modrigais Strauss Nunes & Susana Carla Farias Pereira, 2022. "Intellectual structure and trends in the humanitarian operations field," Annals of Operations Research, Springer, vol. 319(1), pages 1099-1157, December.
    11. McLevey, John & McIlroy-Young, Reid, 2017. "Introducing metaknowledge: Software for computational research in information science, network analysis, and science of science," Journal of Informetrics, Elsevier, vol. 11(1), pages 176-197.
    12. Jacob Wood & Gohar Feroz Khan, 2015. "International trade negotiation analysis: network and semantic knowledge infrastructure," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 537-556, October.
    13. Piñeiro-Chousa, Juan & López-Cabarcos, M. Ángeles & Romero-Castro, Noelia María & Pérez-Pico, Ada María, 2020. "Innovation, entrepreneurship and knowledge in the business scientific field: Mapping the research front," Journal of Business Research, Elsevier, vol. 115(C), pages 475-485.
    14. Akinpelu, O.A. & Olaleye, O. & Fagbola, O., 2023. "The Soil Organic Matter Decomposers: A Bibliometric Analysis," International Journal of Agriculture and Environmental Research, Malwa International Journals Publication, vol. 9(4), August.
    15. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    16. Gaviria-Marin, Magaly & Merigó, José M. & Baier-Fuentes, Hugo, 2019. "Knowledge management: A global examination based on bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 194-220.
    17. Duan, Zhengxiao & Zhang, Yanni & Deng, Jun & Shu, Pan & Yao, Di, 2023. "A systematic exploration of mapping knowledge domains for free radical research related to coal," Energy, Elsevier, vol. 282(C).
    18. Zhichao Wang & Valentin Zelenyuk, 2021. "Performance Analysis of Hospitals in Australia and its Peers: A Systematic Review," CEPA Working Papers Series WP012021, School of Economics, University of Queensland, Australia.
    19. Ignacio Rodríguez-Rodríguez & José-Víctor Rodríguez & Niloofar Shirvanizadeh & Andrés Ortiz & Domingo-Javier Pardo-Quiles, 2021. "Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining," IJERPH, MDPI, vol. 18(16), pages 1-29, August.
    20. Mehdi Toloo & Rouhollah Khodabandelou & Amar Oukil, 2022. "A Comprehensive Bibliometric Analysis of Fractional Programming (1965–2020)," Mathematics, MDPI, vol. 10(11), pages 1-21, May.

    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:gam:jijerp:v:19:y:2022:i:15:p:9711-:d:882100. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.