{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T17:52:12Z","timestamp":1783014732192,"version":"3.54.6"},"reference-count":63,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,23]],"date-time":"2022-02-23T00:00:00Z","timestamp":1645574400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100014684","name":"Region Blekinge","doi-asserted-by":"publisher","award":["Computer aided support for increased knowledge about serial crimes"],"award-info":[{"award-number":["Computer aided support for increased knowledge about serial crimes"]}],"id":[{"id":"10.13039\/501100014684","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The evidence that burglaries cluster spatio-temporally is strong. However, research is unclear on whether clustered burglaries (repeats\/near-repeats) should be treated as qualitatively different crimes compared to spatio-temporally unrelated burglaries (non-repeats). This study, therefore, investigated if there were differences in modus operandi-signatures (MOs, the habits and methods employed by criminals) between near-repeat and non-repeat burglaries across 10 Swedish cities, as well as whether MO-signatures can aid in predicting if a burglary is classified as a near-repeat or a non-repeat crime. Data consisted of 5744 residential burglaries, with 137 MO features characterizing each case. Descriptive data of repeats\/non-repeats is provided together with Wilcoxon tests of MO-differences between crime pairs, while logistic regressions were used to train models to predict if a crime scene was classified as a near-repeat or a non-repeat crime. Near-repeat crimes were rather stylized, showing heterogeneity in MOs across cities, but showing homogeneity within cities at the same time, as there were significant differences between near-repeat and non-repeat burglaries, including subgroups of features, such as differences in mode of entering, target selection, types of goods stolen, as well the traces that were left at the crime scene. Furthermore, using logistic regression models, it was possible to predict near-repeat and non-repeat crimes with a mean F1-score of 0.8155 (0.0866) based on the MO. Potential policy implications are discussed in terms of how data-driven procedures can facilitate analysis of spatio-temporal phenomena based on the MO-signatures of offenders, as well as how law enforcement agencies can provide differentiated advice and response when there is suspicion that a crime is part of a series as opposed to an isolated event.<\/jats:p>","DOI":"10.3390\/ijgi11030160","type":"journal-article","created":{"date-parts":[[2022,2,23]],"date-time":"2022-02-23T09:34:38Z","timestamp":1645608878000},"page":"160","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["All Burglaries Are Not the Same: Predicting Near-Repeat Burglaries in Cities Using Modus Operandi"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8929-7220","authenticated-orcid":false,"given":"Anton","family":"Borg","sequence":"first","affiliation":[{"name":"Blekinge Institute of Technology, 371 79 Karlskrona, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8438-4520","authenticated-orcid":false,"given":"Martin","family":"Svensson","sequence":"additional","affiliation":[{"name":"Blekinge Institute of Technology, 371 79 Karlskrona, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,23]]},"reference":[{"key":"ref_1","unstructured":"Quetelet, A. (1835). Sur L\u2019Homme et le D\u00e9veloppement de ses Facult\u00e9s ou Essai de Physique Sociale, Bachelier, Imprimeur-Libraire."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Andresen, M.A., and Malleson, N. (2013). Spatial Heterogeneity in Crime Analysis. Crime Modeling and Mapping Using Geospatial Technologies, Springer.","DOI":"10.21428\/cb6ab371.27004109"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1093\/bjc\/azh036","article-title":"Prospective Hot-Spotting The Future of Crime Mapping?","volume":"44","author":"Bowers","year":"2004","journal-title":"Br. J. Criminol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1007\/s10940-007-9025-3","article-title":"Space\u2013Time Patterns of Risk: A Cross National Assessment of Residential Burglary Victimization","volume":"23","author":"Johnson","year":"2007","journal-title":"J. Quant. Criminol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.apgeog.2015.03.014","article-title":"Learning where to offend: Effects of past on future burglary locations","volume":"60","author":"Bernasco","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40163-016-0049-6","article-title":"Examining the extent of repeat and near repeat victimisation of domestic burglaries in Belo Horizonte, Brazil","volume":"5","author":"Chainey","year":"2016","journal-title":"Crime Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.apgeog.2013.04.001","article-title":"The space\/time behaviour of dwelling burglars: Finding near repeat patterns in serial offender data","volume":"41","author":"Johnson","year":"2013","journal-title":"Appl. Geogr."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Wang, Z., and Liu, X. (2017). Analysis of burglary hot spots and near-repeat victimization in a large Chinese city. ISPRS Int. J. Geo-Inf., 6.","DOI":"10.3390\/ijgi6050148"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Rossmo, K. (1999). Geographic Profiling, CRC Press.","DOI":"10.1201\/9781420048780"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1018","DOI":"10.1126\/science.1177170","article-title":"Limits of Predictability in Human Mobility","volume":"327","author":"Song","year":"2010","journal-title":"Science"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1108\/PIJPSM-12-2016-0172","article-title":"Examining the extent to which repeat and near repeat patterns can prevent crime","volume":"41","author":"Chainey","year":"2018","journal-title":"Polic. An Int. J."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1007\/s10506-006-9023-z","article-title":"Decision support systems for police: Lessons from the application of data mining techniques to \u201csoft\u201d forensic evidence","volume":"14","author":"Oatley","year":"2006","journal-title":"Artif. Intell. Law"},{"key":"ref_13","unstructured":"Roman, J., Reid, S., Reid, J., Chalfin, A., Adams, W., and Knight, C. (2022, January 31). The DNA Field Experiment: Cost-Effectiveness Analysis of the Use of DNA in the Investigation of High-Volume Crimes, Available online: https:\/\/www.ojp.gov\/pdffiles1\/nij\/grants\/222318.pdf."},{"key":"ref_14","unstructured":"O\u2019Hara, C., and O\u2019Hara, G. (1956). Fundamentals of Criminal Investigation, Charles C Thomas Publisher Ltd.. [7th ed.]."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1348\/135532506X118631","article-title":"The psychology of linking crimes: A review of the evidence","volume":"12","author":"Woodhams","year":"2010","journal-title":"Leg. Criminol. Psychol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1348\/135532508X349336","article-title":"Addressing problems with traditional crime linking methods using receiver operating characteristic analysis","volume":"14","author":"Bennell","year":"2010","journal-title":"Leg. Criminol. Psychol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1069","DOI":"10.1177\/0093854811418599","article-title":"Linking Different Types of Crime Using Geographical and Temporal Proximity","volume":"38","author":"Tonkin","year":"2011","journal-title":"Crim. Justice Behav."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/BF02802858","article-title":"Reliability, Validity, and Utility of Criminal Profiling Typologies","volume":"17","author":"Godwin","year":"2002","journal-title":"J. Police Crim. Psychol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"167","DOI":"10.3233\/IDA-163220","article-title":"Predicting burglars\u2019 risk exposure and level of pre-crime preparation using crime scene data","volume":"22","author":"Boldt","year":"2018","journal-title":"Intell. Data Anal."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.apgeog.2015.08.004","article-title":"A discrete spatial choice model of burglary target selection at the house-level","volume":"64","author":"Vandeviver","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_21","first-page":"12","article-title":"Who commits near repeats? A test of the boost explanation","volume":"5","author":"Bowers","year":"2004","journal-title":"West. Criminol. Rev."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"507","DOI":"10.2307\/2946686","article-title":"Crime and social interactions","volume":"111","author":"Glaeser","year":"1996","journal-title":"Q. J. Econ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1111\/rssa.12076","article-title":"Partially supervised spatiotemporal clustering for burglary crime series identification","volume":"178","author":"Reich","year":"2015","journal-title":"J. R. Stat. Soc. Ser. A Stat. Soc."},{"key":"ref_24","unstructured":"Brantingham, P., and Brantingham, P. (2013). Crime pattern theory. Environmental Criminology and Crime Analysis, Willan."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Becker, G.S. (1968). Crime and Punishment: An Economic Approach. The Economic Dimensions of Crime, Palgrave Macmillan UK.","DOI":"10.1007\/978-1-349-62853-7_2"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"588","DOI":"10.2307\/2094589","article-title":"Social Change and Crime Rate Trends: A Routine Activity Approach","volume":"44","author":"Cohen","year":"1979","journal-title":"Am. Sociol. Rev."},{"key":"ref_27","first-page":"1","article-title":"Introduction: Criminology, Routine Activity, and Rational Choice","volume":"5","author":"Clarke","year":"1993","journal-title":"Routine Act. Ration. Choice Adv. Criminol. Theory"},{"key":"ref_28","first-page":"259","article-title":"Environment, Routine, and Situation: Toward a Pattern Theory of Crime","volume":"5","author":"Brantingham","year":"1993","journal-title":"Routine Act. Ration. Choice"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Johnson, S.D., Bowers, K.J., Birks, D.J., and Pease, K. (2009). Predictive Mapping of Crime by ProMap: Accuracy, Units of Analysis, and the Environmental Backcloth. Putting Crime in its Place, Springer New York.","DOI":"10.1007\/978-0-387-09688-9_8"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1111\/1745-9125.12071","article-title":"Biting once, twice: The influence of prior on subsequent crime location choice","volume":"53","author":"Lammers","year":"2015","journal-title":"Criminology"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1162\/154247603322390982","article-title":"The social multiplier","volume":"1","author":"Glaeser","year":"2003","journal-title":"J. Eur. Econ. Assoc."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"615","DOI":"10.1093\/bjc\/43.3.615","article-title":"Infectious Burglaries. A Test of the Near Repeat Hypothesis","volume":"43","author":"Townsley","year":"2003","journal-title":"Br. J. Criminol."},{"key":"ref_33","unstructured":"Farrell, G., and Pease, K. (1993). Once Bitten, Twice Bitten: Repeat Victimisation and Its Implications for Crime Prevention, Crime Prevention Unit, Paper 46."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1177\/0022427810384136","article-title":"Testing the stability of crime patterns: Implications for theory and policy","volume":"48","author":"Andresen","year":"2011","journal-title":"J. Res. Crime Delinq."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.apgeog.2012.07.007","article-title":"The (in) appropriateness of aggregating across crime types","volume":"35","author":"Andresen","year":"2012","journal-title":"Appl. Geogr."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1080\/15614263.2013.874169","article-title":"The law of concentrations of crime at place: The case of Tel Aviv-Jaffa","volume":"15","author":"Weisburd","year":"2014","journal-title":"Police Pract. Res."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.apgeog.2018.08.001","article-title":"A spatio-temporal kernel density estimation framework for predictive crime hotspot mapping and evaluation","volume":"99","author":"Hu","year":"2018","journal-title":"Appl. Geogr."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1109\/TSMCC.2003.809867","article-title":"A decision model for spatial site selection by criminals: A foundation for law enforcement decision support","volume":"33","author":"Xue","year":"2003","journal-title":"Syst. Man Cybern. Part C Appl. Rev. IEEE Trans."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Wang, S., Li, X., Cai, Y., and Tian, J. (2011, January 24\u201326). Spatial and temporal distribution and statistic method applied in crime events analysis. Proceedings of the 2011 19th International Conference on Geoinformatics, Shanghai, China.","DOI":"10.1109\/GeoInformatics.2011.5980722"},{"key":"ref_40","unstructured":"Zhou, G., Lin, J., and Zheng, W. (2012, January 19\u201321). A web-based geographical information system for crime mapping and decision support. Proceedings of the 2012 International Conference on Computational Problem-Solving (ICCP), Leshan, China."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/s10707-010-0116-1","article-title":"Crime analysis through spatial areal aggregated density patterns","volume":"15","author":"Phillips","year":"2011","journal-title":"Geoinformatica"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Chainey, S., and Ratcliffe, J. (2005). GIS and Crime Mapping, John Wiley & Sons, Ltd.","DOI":"10.1002\/9781118685181"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Glasner, P., and Leitner, M. (2017). Evaluating the impact the weekday has on near-repeat victimization: A spatio-temporal analysis of street robberies in the city of Vienna, Austria. ISPRS Int. J. Geo-Inf., 6.","DOI":"10.3390\/ijgi6010003"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1375\/acri.40.1.1","article-title":"When Does Repeat Burglary Victimisation Occur?","volume":"40","author":"Sagovsky","year":"2007","journal-title":"Aust. N. Z. J. Criminol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1002\/jip.120","article-title":"Linking serial residential burglary: Comparing the utility of modus operandi behaviours, geographical proximity, and temporal proximity","volume":"7","author":"Markson","year":"2010","journal-title":"J. Invest. Psychol. Offender Profiling"},{"key":"ref_46","unstructured":"Martin, G. (2010). A Game of Thrones (A Song of Ice and Fire, Book 1), A Song of Ice and Fire, HarperCollins Publishers."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1002\/jip.21","article-title":"Between a ROC and a hard place: A method for linking serial burglaries bymodus operandi","volume":"2","author":"Bennell","year":"2005","journal-title":"J. Investig. Psychol. Offender Profiling"},{"key":"ref_48","unstructured":"Sheskin, D. (2007). Handbook of Parametric and Nonparametric Statistical Procedures, Chapman & Hall."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1002\/ejsp.2420020412","article-title":"Dealing with a common problem in Social science: A simplified rank-biserial coefficient of correlation based on the U statistic","volume":"2","author":"Wendt","year":"1972","journal-title":"Eur. J. Soc. Psychol."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Cohen, J. (2013). Statistical Power Analysis for the Behavioral Sciences, Taylor & Francis.","DOI":"10.4324\/9780203771587"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Flach, P. (2012). Machine Learning: The Art and Science of Algorithms that Make Sense of Data, Cambridge University Press.","DOI":"10.1017\/CBO9780511973000"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Rogati, M., and Yang, Y. (2002, January 4\u20139). High-performing feature selection for text classification. Proceedings of the Eleventh International Conference on Information and Knowledge Management, McLean, VA, USA.","DOI":"10.1145\/584792.584911"},{"key":"ref_53","first-page":"412","article-title":"A comparative study on feature selection in text categorization","volume":"97","author":"Yang","year":"1997","journal-title":"ICML"},{"key":"ref_54","unstructured":"Liu, H., and Motoda, H. (2012). Feature Selection for Knowledge Discovery and Data Mining, Springer."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Fisher, R.A. (1992). Statistical methods for research workers. Breakthroughs in Statistics, Springer.","DOI":"10.1007\/978-1-4612-4380-9_6"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1195","DOI":"10.1073\/pnas.1814092116","article-title":"The harmonic mean p-value for combining dependent tests","volume":"116","author":"Wilson","year":"2019","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_57","unstructured":"Witten, I.H., and Frank, E. (2005). Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann Publications."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"774","DOI":"10.1016\/S0895-4356(01)00341-9","article-title":"Internal validation of predictive models: Efficiency of some procedures for logistic regression analysis","volume":"54","author":"Steyerberg","year":"2001","journal-title":"J. Clin. Epidemiol."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Harrell, F.E. (2001). Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis, Springer.","DOI":"10.1007\/978-1-4757-3462-1"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1016\/j.patrec.2005.10.010","article-title":"An introduction to ROC analysis","volume":"27","author":"Fawcett","year":"2006","journal-title":"Pattern Recognit. Lett."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1080\/10683160902971030","article-title":"Linkage analysis in cases of serial burglary: Comparing the performance of university students, police professionals, and a logistic regression model","volume":"16","author":"Bennell","year":"2010","journal-title":"Psychol. Crime Law"},{"key":"ref_62","unstructured":"Cromwell, P.F., Olson, J.N., and Avary, D.W. (1991). Breaking and Entering: An Ethnographic Analysis of Burglary, Sage."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1023\/A:1013240828824","article-title":"Aoristic Signatures and the Spatio-Temporal Analysis of High Volume Crime Patterns","volume":"18","author":"Ratcliffe","year":"2002","journal-title":"J. Quant. Criminol."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/3\/160\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:25:50Z","timestamp":1760135150000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/11\/3\/160"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,23]]},"references-count":63,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["ijgi11030160"],"URL":"https:\/\/doi.org\/10.3390\/ijgi11030160","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,23]]}}}