{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T04:46:48Z","timestamp":1762058808100,"version":"build-2065373602"},"reference-count":58,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,7,23]],"date-time":"2022-07-23T00:00:00Z","timestamp":1658534400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>News reports in media contain news about society\u2019s social and political conditions. With the help of publicly available digital datasets of events, it is possible to study a complex network of mass violations, i.e., Mass Killings. Multiple approaches have been applied to bring essential insights into the events and involved actors. Power law distribution behavior finds in the tail of actor mention, co-actor mention, and actor degree tells us about the dominant behavior of influential actors that grows their network with time. The United States, France, Israel, and a few other countries have been identified as major players in the propagation of Mass Killing throughout the past 20 years. It is demonstrated that targeting the removal of influential actors may stop the spreading of such conflicting events and help policymakers and organizations. This paper aims to identify and formulate the conflicts with the actor\u2019s perspective at a global level for a period of time. This process is a generalization to be applied to any level of news, i.e., it is not restricted to only the global level.<\/jats:p>","DOI":"10.3390\/e24081017","type":"journal-article","created":{"date-parts":[[2022,7,24]],"date-time":"2022-07-24T22:49:02Z","timestamp":1658702942000},"page":"1017","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Complex Network Analysis of Mass Violation, Specifically Mass Killing"],"prefix":"10.3390","volume":"24","author":[{"given":"Iqra","family":"Erum","sequence":"first","affiliation":[{"name":"School of Computing, National University of Computer and Emerging Sciences (NUCES), Karachi 75270, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0844-4883","authenticated-orcid":false,"given":"Rauf Ahmed Shams","family":"Malick","sequence":"additional","affiliation":[{"name":"School of Computing, National University of Computer and Emerging Sciences (NUCES), Karachi 75270, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0077-9638","authenticated-orcid":false,"given":"Ghufran","family":"Ahmed","sequence":"additional","affiliation":[{"name":"School of Computing, National University of Computer and Emerging Sciences (NUCES), Karachi 75270, Pakistan"}]},{"given":"Hocine","family":"Cherifi","sequence":"additional","affiliation":[{"name":"Laboratoire Electronique, Informatique et Image (Le2i) UMR 6306 CNRS, Universit\u00e9 de Bourgogne, 21078 Dijon, France"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Miller, J.H., and Page, S.E. (2009). Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton University Press.","DOI":"10.1515\/9781400835522"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"012324","DOI":"10.1103\/PhysRevE.95.012324","article-title":"Growing complex network of citations of scientific papers: Modeling and measurements","volume":"95","author":"Golosovsky","year":"2017","journal-title":"Phys. Rev. E"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1080\/19434470903319441","article-title":"An exploratory, dynamic application of Social Network Analysis for modelling the development of Islamist terror-cells in the West","volume":"2","author":"Mullins","year":"2010","journal-title":"Behav. Sci. Terror. Political Aggress."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Sehgal, G., Sharma, K., Chatterjee, A., and Chakraborti, A. (2018, January 28\u201331). Spatio-temporal networks of social conflicts: Analysis and modeling. Proceedings of the 2018 IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Barcelona, Spain.","DOI":"10.1109\/ASONAM.2018.8508266"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-017-09101-8","article-title":"A complex network analysis of ethnic conflicts and human rights violations","volume":"7","author":"Sharma","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"e1256","DOI":"10.1002\/widm.1256","article-title":"Social network analysis: An overview","volume":"8","author":"Tabassum","year":"2018","journal-title":"Wiley Interdiscip. Rev. Data Min. Knowl. Discov."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40649-019-0061-6","article-title":"Complex network of United States migration","volume":"6","author":"Charyyev","year":"2019","journal-title":"Comput. Soc. Netw."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.socnet.2017.03.003","article-title":"Changing times: Migrants\u2019 social network analysis and the challenges of longitudinal research","volume":"53","author":"Ryan","year":"2018","journal-title":"Soc. Netw."},{"key":"ref_9","unstructured":"Staub, E. (2011). The Roots of Evil: The Origins of Genocide and Other Group Violence, Cambridge University Press."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Charny, I.W., Adalian, R.P., Jacobs, S.L., Markusen, E., and Sherman, M.I. (1999). Encyclopedia of Genocide: AH, Abc-Clio.","DOI":"10.5040\/9798400656279"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1017\/S0020818304582061","article-title":"\u201cDraining the Sea\u201d: Mass Killing and Guerrilla Warfare","volume":"58","author":"Valentino","year":"2004","journal-title":"Int. Organ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"111513","DOI":"10.1016\/j.chaos.2021.111513","article-title":"Multi-agent modeling of crowd dynamics under mass shooting cases","volume":"153","author":"Lu","year":"2021","journal-title":"Chaos Solit. Fractals"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Lee, J.Y., Dietz, J.E., and Ostrowski, K. (2018, January 9\u201312). Agent-based modeling for casualty rate assessment of large event active shooter incidents. Proceedings of the 2018 Winter Simulation Conference (WSC), Gothenburg, Sweden.","DOI":"10.1109\/WSC.2018.8632535"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/j.physa.2016.03.066","article-title":"Modeling of agent-based complex network under cyber-violence","volume":"458","author":"Huang","year":"2016","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/s12103-020-09552-2","article-title":"A comparative analysis of foiled and completed mass shootings","volume":"46","author":"Silva","year":"2021","journal-title":"Am. J. Crim. Justice"},{"key":"ref_16","unstructured":"Gonz\u00e1lez, M., and Alf\u00e9rez, G.H. (2020). Application of data science to discover violence-related issues in Iraq. arXiv."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1140\/epjds\/s13688-022-00315-z","article-title":"Understanding peace through the world news","volume":"11","author":"Voukelatou","year":"2022","journal-title":"EPJ Data Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1177\/0731121420964785","article-title":"Information-seeking in the wake of tragedy: An examination of public response to mass shootings using Google Search data","volume":"65","author":"Semenza","year":"2022","journal-title":"Sociol. Perspect."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Ahuja, M., and Sharma, K. (2014). Complex networks: A review. Int. J. Comput. Appl., 101.","DOI":"10.5120\/17765-8882"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3558","DOI":"10.1016\/j.cnsns.2012.01.013","article-title":"A review of power laws in real life phenomena","volume":"17","author":"Pinto","year":"2012","journal-title":"Commun. Nonlinear Sci. Numer. Simul."},{"key":"ref_21","first-page":"16325","article-title":"Combining social network analysis and agent-based modelling to explore dynamics of human interaction: A review","volume":"2","author":"Will","year":"2020","journal-title":"Socio-Environ. Syst. Model."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.tra.2020.07.003","article-title":"Importance rankings of nodes in the China Railway Express network under the Belt and Road Initiative","volume":"139","author":"Zhang","year":"2020","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.jtbi.2013.04.033","article-title":"Robustness of empirical food webs with varying consumer\u2019s sensitivities to loss of resources","volume":"333","author":"Bellingeri","year":"2013","journal-title":"J. Theor. Biol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ecolmodel.2012.12.011","article-title":"Increasing the extinction risk of highly connected species causes a sharp robust-to-fragile transition in empirical food webs","volume":"251","author":"Bellingeri","year":"2013","journal-title":"Ecol. Model."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1108\/OIR-03-2018-0068","article-title":"A bibliometric analysis of event detection in social media","volume":"43","author":"Chen","year":"2019","journal-title":"Online Inf. Rev."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1073\/pnas.1811388115","article-title":"Integration in emerging social networks explains academic failure and success","volume":"116","author":"Stadtfeld","year":"2019","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1093\/bib\/bbz011","article-title":"Computational methods for identifying the critical nodes in biological networks","volume":"21","author":"Liu","year":"2020","journal-title":"Brief. Bioinform."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Kim, H., Mu\u00f1oz, S., Osuna, P., and Gershenson, C. (2020). Antifragility Predicts the Robustness and Evolvability of Biological Networks through Multi-class Classification with a Convolutional Neural Network. Entropy, 22.","DOI":"10.3390\/e22090986"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"343","DOI":"10.3389\/fgene.2020.00343","article-title":"A Novel Computational Approach for Identifying Essential Proteins From Multiplex Biological Networks","volume":"11","author":"Zhao","year":"2020","journal-title":"Front. Genet."},{"key":"ref_30","unstructured":"Creswell, J.W., and Clark, V.L.P. (2017). Designing and Conducting Mixed Methods Research, Sage Publications."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1037\/tam0000128","article-title":"Beyond first-person shooter video games: Using computational modeling and simulation of mass violence for threat assessment and management","volume":"6","author":"Briggs","year":"2019","journal-title":"J. Threat. Assess. Manag."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1086\/597791","article-title":"Murder by structure: Dominance relations and the social structure of gang homicide","volume":"115","author":"Papachristos","year":"2009","journal-title":"Am. J. Sociol."},{"key":"ref_33","first-page":"101","article-title":"Evolving networks and social network analysis methods and techniques","volume":"101","author":"Cordeiro","year":"2018","journal-title":"Soc. Media Journal. Trends Connect. Implic."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1016\/j.ins.2019.10.003","article-title":"Identification of influencers in complex networks by local information dimensionality","volume":"512","author":"Wen","year":"2020","journal-title":"Inf. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"073407","DOI":"10.1088\/1742-5468\/aace08","article-title":"M-centrality: Identifying key nodes based on global position and local degree variation","volume":"2018","author":"Ibnoulouafi","year":"2018","journal-title":"J. Stat. Mech. Theory Exp."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1007\/s41109-021-00405-3","article-title":"BC tree-based spectral sampling for big complex network visualization","volume":"6","author":"Hu","year":"2021","journal-title":"Appl. Netw. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s41109-021-00430-2","article-title":"Revealing the component structure of the world air transportation network","volume":"6","author":"Diop","year":"2021","journal-title":"Appl. Netw. Sci."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s41109-019-0238-9","article-title":"On community structure in complex networks: Challenges and opportunities","volume":"4","author":"Cherifi","year":"2019","journal-title":"Appl. Netw. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"388","DOI":"10.1016\/j.physa.2004.04.031","article-title":"Error and attack tolerance of complex networks","volume":"340","author":"Crucitti","year":"2004","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"026103","DOI":"10.1103\/PhysRevE.76.026103","article-title":"Error and attack tolerance of layered complex networks","volume":"76","author":"Kurant","year":"2007","journal-title":"Phys. Rev. E"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1016\/j.cnsns.2013.08.028","article-title":"Information spreading on dynamic social networks","volume":"19","author":"Liu","year":"2014","journal-title":"Commun. Nonlinear Sci. Numer. Simul."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"139636","DOI":"10.1109\/ACCESS.2021.3119404","article-title":"Complex Network and Source Inspired COVID-19 Fake News Classification on Twitter","volume":"9","author":"Qureshi","year":"2021","journal-title":"IEEE Access"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Chakraborty, D., Singh, A., and Cherifi, H. (2016, January 2\u20134). Immunization strategies based on the overlapping nodes in networks with community structure. Proceedings of the International Conference on Computational Social Networks, Ho Chi Minh City, Vietnam.","DOI":"10.1007\/978-3-319-42345-6_6"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Kumar, M., Singh, A., and Cherifi, H. (2018, January 23\u201327). An efficient immunization strategy using overlapping nodes and its neighborhoods. Proceedings of the Companion Proceedings of the The Web Conference 2018, Lyon, France.","DOI":"10.1145\/3184558.3191566"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"42431","DOI":"10.1038\/srep42431","article-title":"Network growth models: A behavioural basis for attachment proportional to fitness","volume":"7","author":"Bell","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Shafie, T. (2015). A Multigraph Approach to Social Network Analysis. J. Soc. Struct., 16.","DOI":"10.21307\/joss-2019-011"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1348\/000711099159053","article-title":"Logit models and logistic regressions for social networks: II. Multivariate relations","volume":"52","author":"Pattison","year":"1999","journal-title":"Br. J. Math. Stat. Psychol."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Wasserman, S., and Faust, K. (1994). Wasserman, Stanley, and Katherine Faust, Social Network Analysis: Methods and Applications, Cambridge University Press.","DOI":"10.1017\/CBO9780511815478"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1007\/s10044-019-00820-4","article-title":"Finding patterns in the degree distribution of real-world complex networks: Going beyond power law","volume":"23","author":"Chattopadhyay","year":"2019","journal-title":"Pattern Anal. Appl."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1137\/070710111","article-title":"Power-law distributions in empirical data","volume":"51","author":"Clauset","year":"2009","journal-title":"SIAM Rev."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1740007","DOI":"10.1142\/S2424942417400072","article-title":"Fat tailed distributions for deaths in conflicts and disasters","volume":"1","author":"Chatterjee","year":"2017","journal-title":"Rep. Adv. Phys. Sci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1140\/epjb\/e2007-00219-y","article-title":"Parameter estimation for power-law distributions by maximum likelihood methods","volume":"58","author":"Bauke","year":"2007","journal-title":"Eur. Phys. J. B"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Alstott, J., Bullmore, E., and Plenz, D. (2014). powerlaw: A Python package for analysis of heavy-tailed distributions. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0085777"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"104773","DOI":"10.1109\/ACCESS.2021.3094196","article-title":"A Survey on Centrality Metrics and Their Network Resilience Analysis","volume":"9","author":"Wan","year":"2021","journal-title":"IEEE Access"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"10088","DOI":"10.1038\/s41598-021-89549-x","article-title":"Characterizing the interactions between classical and community-aware centrality measures in complex networks","volume":"11","author":"Rajeh","year":"2021","journal-title":"Sci. Rep."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-019-47119-2","article-title":"The heterogeneity in link weights may decrease the robustness of real-world complex weighted networks","volume":"9","author":"Bellingeri","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1007\/s10559-020-00247-4","article-title":"Vulnerability of Complex Network Structures and Systems","volume":"56","author":"Polishchuk","year":"2020","journal-title":"Cybern. Syst. Anal."},{"key":"ref_58","unstructured":"Halkia, M., Ferri, S., Papazoglou, M., Van Damme, M.S., and Thomakos, D. (2020, January 11\u201316). Conflict Event Modelling: Research Experiment and Event Data Limitations. Proceedings of the Workshop on Automated Extraction of Socio-Political Events from News 2020, Marseille, France."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/24\/8\/1017\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:55:32Z","timestamp":1760140532000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/24\/8\/1017"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,23]]},"references-count":58,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2022,8]]}},"alternative-id":["e24081017"],"URL":"https:\/\/doi.org\/10.3390\/e24081017","relation":{},"ISSN":["1099-4300"],"issn-type":[{"type":"electronic","value":"1099-4300"}],"subject":[],"published":{"date-parts":[[2022,7,23]]}}}