Geolocalized mafia homicides in Palermo (1950–2020): insights into the evolution of Cosa Nostra

Geolocalized mafia homicides in Palermo (1950–2020): insights into the evolution of Cosa Nostra | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Geolocalized mafia homicides in Palermo (1950–2020): insights into the evolution of Cosa Nostra Giuseppe Glaviano, Dario Zarcone, Francesco Petruzzella, Ludovica d'Alessio, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9301845/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract We investigate the statistical properties of mafia-related homicidal events occurred in the city of Palermo (Italy) from 1950 to 2020. Such data are extracted from a unique electronic archive containing microdata on mafia-related homicides, attempted homicides and disappearances committed in Sicily. This electronic archive is maintained by the Palermo Prosecutor’s Office (Direzione Distrettuale Antimafia) and is regularly consulted by magistrates investigating crimes associated with Cosa Nostra. Specifically, we aim to understand how geolocalizing homicides within the greater Palermo area can assist researchers and law enforcement authorities (Judiciary and Law Enforcement Agencies) in better characterizing and potentially predicting the temporal (micro-)patterns of crimes perpetrated by Cosa Nostra syndicates. To this end, we combine homicidal microdata with population density data at the submunicipal level of neighbourhoods (quartieri). This integration allows us to identify areas where the incidence of homicides is significantly higher or lower than expected under a null hypothesis of random distribution, adjusted for the actual population density in Palermo. In this way, we highlight neighbourhoods disproportionately affected by homicidal events, not in absolute terms, but relative to local population figures during a certain time period. The time periods we are considering are obtained by using an unsupervised statistical procedure that is able to highlight the temporal points when the statistical properties of the homicidal time series changes its statistical properties. The underlying idea is that such changes are associated to a regime shift in the Cosa Nostra criminal activities. The analyses presented in this paper may be usefully employed, at the very least, to reconstruct the broader context in which homicides occur. Complex Networks Cosa Nostra geolocalization crime homicides statistical validation change-points Law Enforcement Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 01 May, 2026 Reviewers agreed at journal 22 Apr, 2026 Reviewers invited by journal 20 Apr, 2026 Editor assigned by journal 07 Apr, 2026 Submission checks completed at journal 07 Apr, 2026 First submitted to journal 02 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9301845","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":628550327,"identity":"b2633337-79f0-41f5-9070-f754f38deb20","order_by":0,"name":"Giuseppe Glaviano","email":"","orcid":"","institution":"University of Palermo","correspondingAuthor":false,"prefix":"","firstName":"Giuseppe","middleName":"","lastName":"Glaviano","suffix":""},{"id":628550328,"identity":"5acd5dae-5799-4f67-9ef2-8eebd326770f","order_by":1,"name":"Dario Zarcone","email":"","orcid":"","institution":"University of 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Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Complex Networks, Cosa Nostra, geolocalization, crime, homicides, statistical validation, change-points, Law Enforcement","lastPublishedDoi":"10.21203/rs.3.rs-9301845/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9301845/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe investigate the statistical properties of mafia-related homicidal events\u0026nbsp;occurred in the city of Palermo (Italy) from 1950 to 2020. Such data are\u0026nbsp;extracted from a unique electronic archive containing microdata on mafia-related\u0026nbsp;homicides, attempted homicides and disappearances committed in Sicily. This\u0026nbsp;electronic archive is maintained by the Palermo Prosecutor’s Office (Direzione\u0026nbsp;Distrettuale Antimafia) and is regularly consulted by magistrates investigating\u0026nbsp;crimes associated with Cosa Nostra.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSpecifically, we aim to understand how geolocalizing homicides within the greater Palermo area can assist researchers and law enforcement authorities (Judiciary and Law Enforcement Agencies) in better characterizing and potentially predicting the temporal (micro-)patterns of crimes perpetrated by Cosa Nostra \u0026nbsp;syndicates.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo this end, we combine homicidal microdata with population density data at the submunicipal level of neighbourhoods (quartieri). This integration allows us\u0026nbsp;to identify areas where the incidence of homicides is significantly higher or lower\u0026nbsp;than expected under a null hypothesis of random distribution, adjusted for the\u0026nbsp;actual population density in Palermo. In this way, we highlight neighbourhoods disproportionately affected by homicidal events, not in absolute terms, but relative to local population figures during a certain time period. The time periods\u0026nbsp;we are considering are obtained by using an unsupervised statistical procedure\u0026nbsp;that is able to highlight the temporal points when the statistical properties of\u0026nbsp;the homicidal time series changes its statistical properties. The underlying idea is that such changes are associated to a regime shift in the Cosa Nostra criminal\u0026nbsp;activities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe analyses presented in this paper may be usefully employed, at the very least,\u0026nbsp;to reconstruct the broader context in which homicides occur.\u003c/p\u003e","manuscriptTitle":"Geolocalized mafia homicides in Palermo (1950–2020): insights into the evolution of Cosa Nostra","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-27 11:42:05","doi":"10.21203/rs.3.rs-9301845/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"14476054802581853374446031873594694369","date":"2026-05-01T04:55:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"195793411795365048493350901235955866612","date":"2026-04-22T18:07:44+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-20T13:29:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-07T07:25:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-07T07:24:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"EPJ Data Science","date":"2026-04-02T10:20:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"epj-data-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"epds","sideBox":"Learn more about [EPJ Data Science](https://epjdatascience.springeropen.com/)","snPcode":"13688","submissionUrl":"https://submission.springernature.com/new-submission/13688/3","title":"EPJ Data Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Open","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f9045afa-5fa0-42ca-a617-31da5f5ae574","owner":[],"postedDate":"April 27th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"14476054802581853374446031873594694369","date":"2026-05-01T04:55:17+00:00","index":20,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-27T11:42:05+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-27 11:42:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9301845","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9301845","identity":"rs-9301845","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}