Relevant bibliographies by topics / Crime analysis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Crime analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 29 July 2024

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Journal articles on the topic "Crime analysis"

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Evtushenko, I. I. "SITUATION AND ANALYSIS OF CRIMES AGAINST PROPERTY IN THE REPUBLIC OF CRIMEA (FOR THE PERIOD FROM 2015 TO 2020)." Scientific Notes of V. I. Vernadsky Crimean Federal University. Juridical science 7 (73), no. 3 (1) (2022): 170–80. http://dx.doi.org/10.37279/2413-1733-2021-7-3(1)-170-180.

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A criminological analysis of the situation and dynamics of crime against property in the Republic of Crimea (for the period from 2015 to 2020) in comparison with all-Russian indicators and indicators of the Southern Federal District was carried out, similar features and differences were identified, an attempt was made to study the causal complex, events in the Republic of Crimea that could affect the dynamics and level of mercenary crime in different periods of time. The analysis was carried out for each type of crimes against property provided for by the Criminal Code of the Russian Federation, in their interrelation, as well as an analysis of the situation as a whole. In this connection, the author analyzed crimes against property according to two criminological indicators: the dynamics is an absolute indicator of the total number of registered acts for the period from 2015 to 2020 inclusive, and the level is a relative indicator of a particular type of crime in the overall crime structure. This approach allowed us to objectively study the criminological indicators of certain types of crimes against property and draw general conclusions, identify patterns that determine the development of the criminal situation in the field of mercenary crime in the Republic of Crimea.
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Kumrinisa, Abdurasulova. "ANALYSIS OF QUANTITATIVE AND QUALITATIVE INDICATORS OF WOMEN'S CRIME." International Journal of Law And Criminology 3, no. 12 (December 1, 2023): 16–22. http://dx.doi.org/10.37547/ijlc/volume03issue12-04.

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The article provides an analysis of the quantitative and qualitative features of female crime. The socio-psychological determinants of female criminal activity are given. The main types of crimes committed by women are considered. The emphasis is placed on the fact that preventing violent crime among women is an important factor in curbing crime in general. The crime of women differs from the crime of men in its quantitative indicators, the nature of the crimes and their consequences, the methods and instruments of commission, the role played by women,the choice of the victim of a criminal attack, the influence of family and household circumstances and accompanying circumstances on the crime.
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Swamy, Mr K. K., Mrs SRILATHA PULI, S. SWETHA, B. SHARANYA, A. ANUHYA, and J. SHREYAS. "CRIME ANALYSIS USING MACHINE LEARNING." YMER Digital 21, no. 05 (May 10, 2022): 412–16. http://dx.doi.org/10.37896/ymer21.05/44.

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Crimes are the significant threat to the humankind. as crimes are increasing at a rapid rate approach for identifying trends in crime. Our project can predict regions which have high probability for crime occurrence and can visualize crime prone areas by visual representation of data by bar graphs, pie charts etc. It speed up the classification of criminal activities by calculating the average accuracy rate .It uses crime data set and predicts the types of crimes in a particular area which help in Accurate results based on the predictive analysis of logistic regression. The objective would be train a model for prediction using logistic regression classification algorithm. Logistic regression used for classification problems and it is a predictive analysis algorithm based on concept of probability. Crime analysis project is a systematic approach for identifying trends in crime. .It uses crime data set and predicts the types of crimes in a particular area which help in Accurate results based on the predictive analysis of logistic regression.
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Lakušić, Milovan, Sofija Lolić, and Julijana Račić. "Analysis and assessment of money laundering risks." Megatrend revija 19, no. 3 (2022): 171–82. http://dx.doi.org/10.5937/megrev2202171l.

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In this paper, money laundering is primarily highlighted as a crime, the concept and essence of this crime. Due to the prevalence of this crime, at the national and international level, the chapter is dedicated to the analysis and assessment of the risk of money laundering, as something that is constantly working on government agencies and international organizations. The crime of money laundering is associated with a large number of crimes against the economy as well as certain corrupt crimes, and it is necessary to determine the degree of danger of other crimes that are committed in order to commit the crime of money laundering. As a crime whose means of execution are constantly adjusted, this crime is most often committed by organized criminal groups, and prevention is extremely important when it comes to this crime.
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Et. al., R. Ananda DhanaLakshmi,. "COMPARATIVE ANALYSIS OF CRIME TYPE PREDICTION." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 2 (April 11, 2021): 963–67. http://dx.doi.org/10.17762/itii.v9i2.437.

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Crime analysis and prediction is a logical approach for analysing and identifying different patterns, relationships and trends in crime. The system can predict the area which have high probability for crime occurrence and indicate crime prone areas. It will be useful for the law enforcement agencies to speed up the process of solving crimes with the increasing computerized systems and with the help of crime data analysts. Here we have an approach between computer science and criminal justice to develop a data mining procedure that can help solve crimes faster. Analysis of police data createawareness that lets officers track criminal activities, predict the incidents, effectively deploy resources and solve cases faster. In this paper crime analysis is done by k-means,Spectral clustering and Agglomerative clustering on the crime dataset.
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Lama, Swikar, and Sikandar Singh Rathore. "Crime Mapping and Crime Analysis of Property Crimes in Jodhpur." International Annals of Criminology 55, no. 2 (November 2017): 205–19. http://dx.doi.org/10.1017/cri.2017.11.

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AbstractThis study is based on crime mapping and crime analysis of property crimes in Jodhpur. The property crimes which were selected were house breaking, auto thefts and chain snatching. Data from police stations were used to generate the maps to locate hot spots of crimes. The profile of these hot spots was analyzed through observations supplemented with interviews of police officers and public 100 cases of house breaking and 100 cases of auto thefts were further analyzed to understand the contexts which lead to these crimes. These contexts are in consonance with situational crime prevention theories. This study may help to understand the environmental factors which may be responsible for certain places becoming hot spot areas of property crimes in Jodhpur.
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Lee, Jiyoung, Michael Leitner, and Gernot Paulus. "Spatiotemporal Analysis of Nighttime Crimes in Vienna, Austria." ISPRS International Journal of Geo-Information 13, no. 7 (July 10, 2024): 247. http://dx.doi.org/10.3390/ijgi13070247.

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Studying the spatiotemporal dynamics of crime is crucial for accurate crime geography research. While studies have examined crime patterns related to weekdays, seasons, and specific events, there is a noticeable gap in research on nighttime crimes. This study focuses on crimes occurring during the nighttime, investigating the temporal definition of nighttime crime and the correlation between nighttime lights and criminal activities. The study concentrates on four types of nighttime crimes, assault, theft, burglary, and robbery, conducting univariate and multivariate analyses. In the univariate analysis, correlations between nighttime crimes and nighttime light (NTL) values detected in satellite images and between streetlight density and nighttime crimes are explored. The results highlight that nighttime burglary strongly relates to NTL and streetlight density. The multivariate analysis delves into the relationships between each nighttime crime type and socioeconomic and urban infrastructure variables. Once again, nighttime burglary exhibits the highest correlation. For both univariate and multivariate regression models the geographically weighted regression (GWR) outperforms ordinary least squares (OLS) regression in explaining the relationships. This study underscores the importance of considering the location and offense time in crime geography research and emphasizes the potential of using NTL in nighttime crime analysis.
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Moskaleva, E. G., and N. N. Podol'naya. "CRIMINOLOGICAL ANALYSIS OF ECONOMIC CRIME." Bulletin of Udmurt University. Series Economics and Law 31, no. 1 (February 12, 2021): 117–23. http://dx.doi.org/10.35634/2412-9593-2021-31-1-117-123.

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The article defines the consequences of economic crimes, summarizes the experience of theoretical and empirical studies of crime in the Russian economy, and presents the results of the author's research in this area. The interpretation of the concept of "economic crime" is characterized by legislative, departmental and research approaches. The authors argue that it is difficult to detect crimes in the economic sphere and the high level of latency of economic crime. Data from official statistics of Rosstat and the Prosecutor General's office of the Russian Federation were selected as the empirical base of the study. The research was carried out using methods of visual representation of data, research of dynamics, structure and analysis of relationships in the whole country and in the regional context. The study revealed the main trends in the situation from the point of view of criminalization and de-criminalization of the Russian economy, consisting in slowing down the reduction in the number of crimes in the economy in the Russian Federation. The study identifies regions with an increased level of economic crime and assesses the effectiveness of measures taken to counteract economic crime. The analysis made it possible to determine the directions of countering economic crime in Russia with the mandatory involvement of digital technologies.
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Maurya, Prakash, Tahir Shaikh, Imran Ahmed, Amaan Firdosi, and Prof Kiran Deshmukh. "Crime Analysis and Prediction Using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (April 30, 2023): 1470–73. http://dx.doi.org/10.22214/ijraset.2023.50310.

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Abstract: The aim of this study is to develop a machine learning-based application that can analyze crime data across different districts in India and categorize them as high, moderate, or low based on the frequency of crimes. Based on the frequency of particular crimes in particular districts we will suggest necessary preventive measures and also recommend some precautions before visiting a particular crime hotspot. The methodology involved using a Logistic regression model for crime classification, followed by k-means clustering to group districts based on their crime rates. The results of the study demonstrated the efficacy of the machine learning model in accurately classifying crimes. The original contribution of this research lies in the development of an application that provides users with valuable insights into the crime rates in different districts
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Sonali Pakhmode, Vanshita Gaikwad, Bhargavee Talekar, Neha Golatkar, and Vipin Jaiswal. "Regional Crime Data Analysis and Insights Using Fb Prophet." International Research Journal on Advanced Engineering and Management (IRJAEM) 2, no. 05 (May 17, 2024): 1395–401. http://dx.doi.org/10.47392/irjaem.2024.0192.

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Crime is one of the most dominate and formidable aspect of the society. Crimes are committed daily, which has made the lives of the common people restive. Therefore, preventing the crime from occurring can be achieved through a systematic approach by recognizing and evaluating the criminal trends specific to a certain location. Data analysis can assist us to explore former criminal incidents and help us analyze the patterns and hidden correlations which can be used for prevention of crime. Our system aims to analyze crime-prone regions by using the location and time of the crime. Data visualization is a powerful tool for investigating crime rates across the country. Heat maps can be useful for determining the hotspots of crime. The proposed system analyzes the data using the FBprophet model to forecast crime rates in different regions. The Facebook Prophet library, maintained by Facebook, provides forecasting of time series data. This application uses past data and web-scraped data from various sites in order to get detailed studies of various crimes in multiple places. It also enables you to get data about crimes in many places across India by using the pin codes. Government organizations and police departments can effectively utilize it to monitor crime events within a locality.
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Dissertations / Theses on the topic "Crime analysis"

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Condirston, Erin. "Traditional Crime vs. Corporate Crime: A Comparative Risk Discourse Analysis." Thèse, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/20315.

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With the knowledge that risk has become an omnipresent concept used to understand various social problems, this study aims to fill a perceived gap in literature by investigating the way in which risk discourse is applied to understand different categories of crime, namely traditional crime and corporate crime. It is hypothesized that risk logic is heavily applied to the understanding of traditional crime, with minimal attribution to conversations surrounding corporate crime. The pervasiveness of risk as a technique or tactic of government renders the study of its application to different types of crime an important addition to the existing risk literature. Using the method of a comparative content analysis, the parallels and discrepancies between the ways in which risk is used to discuss traditional and corporate crime by Canadian federal criminal justice organizations are explored. The results indicate a lack of focus on risk logic with respect to corporate crime, but demonstrate that risk discourse is perhaps not altogether absent from corporate crime discussions.
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Polat, Esra. "Spatio-temporal Crime Prediction Model Based On Analysis Of Crime Clusters." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608881/index.pdf.

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Crime is a behavior disorder that is an integrated result of social, economical and environmental factors. In the world today crime analysis is gaining significance and one of the most popular subject is crime prediction. Stakeholders of crime intend to forecast the place, time, number of crimes and crime types to get precautions. With respect to these intentions, in this thesis a spatio-temporal crime prediction model is generated by using time series forecasting with simple spatial disaggregation approach in Geographical Information Systems (GIS). The model is generated by utilizing crime data for the year 2003 in Bahç
elievler and Merkez Ç
ankaya police precincts. Methodology starts with obtaining clusters with different clustering algorithms. Then clustering methods are compared in terms of land-use and representation to select the most appropriate clustering algorithms. Later crime data is divided into daily apoch, to observe spatio-temporal distribution of crime. In order to predict crime in time dimension a time series model (ARIMA) is fitted for each week day, Then the forecasted crime occurrences in time are disagregated according to spatial crime cluster patterns. Hence the model proposed in this thesis can give crime prediction in both space and time to help police departments in tactical and planning operations.
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Zugschwerdt, Marc. "'Designing out Crime' – A Spatial and Temporal Analysis of Crime in Umeå." Thesis, Umeå universitet, Kulturgeografi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-137192.

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The creation of sustainable and safe environments nowadays moves more and more into focus for urban planners and architects. Cities should be designed in a way to contribute to social cohesion, shaping an inclusive environment and focusing on the wellbeing of its citizens. Nevertheless, these processes can be undermined by public crime and the fear of crime, which is not only affecting aspects of personal safety but also affecting the people’s behaviour. Reasons why criminality occurs are manifold, impacted by a dynamic set of socioeconomic, demographic, personal but also environmental aspects. In recent years especially the impact of factors related to urban and environmental design respectively planning received rising attention in the field of crime prevention. However, the implementation of strategies regarding ‘crime prevention through environmental design’ or ‘designing out crime’ is still in its early stage in Sweden.   This study aims to investigate spatial and temporal patterns of public crime for the case of Umeå in order to identify potential risk areas, which could receive particular attention regarding crime prevention through environmental design (CPTED). In this sense a GIS based spatial analysis had the aim to detect statistically significant hotspots of crime and furthermore to assess the development of these hotspots over time. In order to understand the nature of public crime and criminal behaviour in Umeå in a more holistic way, also temporal aspects regarding the occurrence of crime were analysed. One particularly vulnerable neighbourhood was examined with a qualitative field observation regarding the principles of crime prevention through environmental design in order to assess in which way the built environment is designed and suited to prevent and deter criminality.   Umeå displays rather clear patterns of higher crime activity, assigned to seasonal, weakly and daily periods, which are connected to higher activity in the public space. Also from a spatial perspective certain patterns are detectable with a higher vulnerability for crime at spots which generate higher activity such as shopping areas or neighbourhoods with nightlife and transport hub functions, and in general neighbourhoods with a higher building density. The neighbourhood of Ålidhem displayed thereby a high concentration of criminality, marked as a constant or even intensifying hotspot for the entire period of investigation. The results of the field observation regarding principles of CPTED are especially indicating a lack of maintenance and furthermore the street and building layout is contributing to disorientation. On the other hand, the area is in most cases well equipped for natural surveillance and provides a high amount of locations for leisure and recreation in order strengthen social cohesion.
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Chester, Helen Jayne. "Property crime in context : a multi-level analysis of the British Crime Survey." Thesis, University of Manchester, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.520721.

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Van, de Ven Jennifer T. C. "Content analysis of Canadian television crime news." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0011/MQ36854.pdf.

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FICARA, Annamaria. "Social network analysis approaches to study crime." Doctoral thesis, Università degli Studi di Palermo, 2022. http://hdl.handle.net/10447/537005.

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Social Network Analysis (SNA) studies groups of individuals and can be applied in a lot of areas such us organizational studies, psychology, economics, information science and criminology. One of the most important results of SNA has been the definition of a set of centrality measures (e.g., degree, closeness, betweenness, or clustering coefficient) which can be used to identify the most influential people with respect to their network of relationships. The main problem with computing centrality metrics on social networks is the typical big size of the data. From the computational point of view, SNA represents social networks as graphs composed of a set of nodes connected by another set of edges on which the metrics of interest are computed. To overcome the problem of big data, some computationally-light alternatives to the standard measures, such as Game of Thieves or WERW-Kpath, can be studied. In this regard, one of my main research activities was to analyze the correlation among standard and nonstandard centrality measures on network models and real-world networks. The centrality metrics can greatly contribute to intelligence and criminal investigations allowing to identify, within a covert network, the most central members in terms of connections or information flow. Covert networks are terrorist or criminal networks which are built from the criminal relationships among members of criminal organizations. One of the most renowned criminal organizations is the Sicilian Mafia. The focal point of my research work was the creation of two real-world criminal networks from the judicial documents of an anti-mafia operation called Montagna conducted by a specialized anti-mafia police unit of the Italian Carabinieri in Messina (i.e., the third largest city on the island of Sicily). One network includes meetings and the other one records telephone calls among suspected criminals of two Sicilian Mafia families. This dataset is unique and it might represent a valuable resource for better understanding complex criminal phenomena from a quantitative standpoint. Different SNA approaches have been used on these Montagna networks to describe their structure and functioning, to predict missing links, to identify leaders or to evaluate police interventions aimed at dismantling and disrupting the networks. Graph distances have been used to find a network model able to properly mime the structure of a Mafia network and to quantify the impact of incomplete data not only on Mafia networks such as the Montagna ones but also on terrorist and street gangs networks. The two simple Montagna networks have been finally used to build a multilayer network trying to obtain a more nuanced understanding of the network structure and of the strategic position of nodes in the network.
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Payne, Troy C. "Does Changing Ownership Change Crime? An Analysis of Apartment Ownership and Crime in Cincinnati." University of Cincinnati / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1288968354.

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Millar, Jack William Logan. "Beer fronts and crime waves : a GIS analysis of weather, alcohol, and violent crime /." Available to subscribers only, 2008. http://proquest.umi.com/pqdweb?did=1594501421&sid=9&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Nilsson, Linn. "The portrayal of Crime : Printed news media's representation of crime in Malmö." Thesis, Malmö universitet, Institutionen för kriminologi (KR), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-45495.

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In today's modern society we are highly exposed to different media in our everyday life, and individuals may spend a large part of their time taking part in media debates, news and other information shared on different media channels. Through this, news media have become an influential factor for how individuals in today's society perceive and construct reality, and consequently the public's perception of crime. This critical analysis strives to elucidate how crime in Malmö is presented in Swedish newspapers. This report is centered on which discourses emerge throughout the chosen empirical material, how different crime types are presented and how victims and perpetrators are constructed in this material. By studying how Malmö is presented through a commonly used news media source, it is possible to uncover how collective understandings of crime are created and affirmed, which is essential in order to be able to influence this established (but arguably somewhat radical) image. Newspapers' presentation of Malmö differs from the description of other major cities in Sweden, and Malmö is often illustrated as a dangerous or unsafe city with high crime rates. The perception of crime in Malmö given through the official statistics are overshadowed by news media's accentuation of violent and lethal crime. A skewed division of crime reporting, may therefore be an important factor for the public's perception of crime in Malmö. Crimes are depicted as an effect of larger societal problems and an integral part of everyday life. Few articles dispute the established image of Malmö as dangerous, and the few who do only briefly highlight this to an extremely limited extent, resulting in the preservation and reproduction of the majority's presentation of Malmö as a dangerous or unsecure city.
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Sundberg, Jacob. "Linking crime through modus operandi. On linking Series of Crime into Single Offenders through Sructured Collection of Crime Scene Information." Thesis, Malmö universitet, Fakulteten för hälsa och samhälle (HS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-25526.

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The current paper is aimed at providing an overview of the current state of research regarding the potential of linking series of crimes to single offenders through repeated modus operandi behaviors. A systematic literature review was conducted to document findings from previous evaluation research as to the predictive accuracy of crime linkage specific to residential burglary. The findings indicate that predictions of linked burglaries can be made with moderate to high predictive accuracy. In order to get an understanding of the extent to which residential burglary offenders repeat their crime scene behaviors, the findings are discussed in relation to the criminological theories Routine activities theory and the Rational Choice perspective. Future research is suggested.
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Books on the topic "Crime analysis"

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Haelterman, Harald. Crime Script Analysis. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-54613-5.

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1971-, Nahoun Joel D., ed. Applied crime analysis. Boston: Butterworth-Heinemann, 2001.

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Burrows, John. Retail crime: Prevention through crime analysis. London: Home Office, 1988.

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Grana, Glenn, and James Windell. Crime and Intelligence Analysis. Boca Raton, FL : CRC Press, 2017.: Routledge, 2016. http://dx.doi.org/10.1201/9781315380766.

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Walker, Jeffery T., and Grant R. Drawve. Foundations of Crime Analysis. Abingdon, Oxon; New York, NY: Routledge, 2018.: Routledge, 2018. http://dx.doi.org/10.4324/9781315716442.

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National Center for the Analysis of Violent Crime (U.S.), ed. VICAP crime analysis report. [Quantico, Va.?]: U.S. Dept. of Justice, Federal Bureau of Investigation, National Center for the Analysis of Violent Crime, 1991.

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Nick, Tilley, ed. Analysis for crime prevention. Monsey, NY: Criminal Justice Press, 2002.

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Kalish, Carol B. International crime rates. [Washington, D.C.]: U.S. Dept. of Justice, Bureau of Justice Statistics, 1988.

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Catriona, Mirrlees-Black, and Great Britain. Home Office. Research and Planning Unit., eds. Racially motivated crime: A British Crime Survey analysis. London: Home Office, 1994.

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Sean, Bair, and Helms Dan, eds. Tactical crime analysis: Research and investigation. Boca Raton: Taylor & Francis, 2010.

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Book chapters on the topic "Crime analysis"

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Dörmann, U. "Crime Analysis." In Police Research in the Federal Republic of Germany, 49–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-74176-0_4.

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Fennelly, Lawrence J., and Marianna A. Perry. "Crime Analysis." In Security Officers and Supervisors, 151. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.4324/9781003402718-66.

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Walker, Jeffery T., and Grant R. Drawve. "Crime mapping." In Foundations of Crime Analysis, 188–205. Abingdon, Oxon; New York, NY: Routledge, 2018.: Routledge, 2018. http://dx.doi.org/10.4324/9781315716442-12.

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Haelterman, Harald. "Crime and Criminality." In Crime Script Analysis, 27–111. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-54613-5_3.

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Keatley, David. "Crime Script Analysis." In Pathways in Crime, 125–36. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75226-6_10.

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Keatley, David. "Crime Linkage Analysis." In Pathways in Crime, 137–46. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75226-6_11.

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Walker, Jeffery T., and Grant R. Drawve. "Describing crime events." In Foundations of Crime Analysis, 87–116. Abingdon, Oxon; New York, NY: Routledge, 2018.: Routledge, 2018. http://dx.doi.org/10.4324/9781315716442-7.

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Haelterman, Harald. "Scripting Crime Against Business." In Crime Script Analysis, 113–59. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-54613-5_4.

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Haelterman, Harald. "Introduction." In Crime Script Analysis, 1–6. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-54613-5_1.

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Haelterman, Harald. "Crimes as Scripts." In Crime Script Analysis, 7–26. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-137-54613-5_2.

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Conference papers on the topic "Crime analysis"

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Da Silveira, Márcio V. C., and Wladmir C. Brandão. "Characterizing Crimes from Web." In VI Brazilian Workshop on Social Network Analysis and Mining. Sociedade Brasileira de Computação - SBC, 2017. http://dx.doi.org/10.5753/brasnam.2017.3249.

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Crime prevention requires the effective use of police resources, which demands the access of criminal information for planning security actions. The number of crime occurrences is higher than the official reported numbers. Many victims do not report crimes directly to the security agencies. Instead, they prefer to anonymously report using different channels, such as the Web. In this article, we introduce our approach to characterize crimes reported in the Web. Particularly, we collect criminal data from popular websites that store crime occurrences, and we use clustering analysis to discover crime patterns on the collected data. Applying our approach to a popular Brazilian crime report website, we observe that more than 41% of the crimes were not reported to the security agencies, and most of them are thefts and robberies occurring at night and dawn. In addition, minor offenses present different patterns of serious crimes. Moreover, crime patterns are different in rich and poor neighborhood.
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Garcia-Zanabria, Germain, and Luis Gustavo Nonato. "Visual crime pattern analysis." In Anais Estendidos da Conference on Graphics, Patterns and Images. Sociedade Brasileira de Computação - SBC, 2022. http://dx.doi.org/10.5753/sibgrapi.est.2022.23261.

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Studying and analyzing crime patterns in big cities is a challenging Spatio-temporal problem. The problem’s difficulty is linked to different factors such as data modeling, unsophisticated hotspot detection techniques, Spatio-temporal patterns, and study delimitation. Previous works have mostly focused on the analysis of crimes with the intent of uncovering patterns associated to social factors, seasonality, and urban activities in whole districts, regions, and neighborhoods. Those tools can hardly allow micro-scale crime analysis closely related to crime opportunity, whose understanding is fundamental for planning preventive actions. Visualizing different patterns hidden in crime time series data is another issue in this context, mainly due to the number of patterns that can show up in the time series analysis. In this dissertation, we propose a set of approaches for interactive visual crime analysis. Relying on machine learning methods, statistical and mathematical mechanisms, and visualization, each proposed methodology focus on solving specific crime-related problems. These proposed tools to explore specific city locations turned out to be essential for domain experts to accomplish their analysis in a bottom-up fashion, revealing how urban features related to mobility, passerby behavior, and the presence of public infrastructures can influence the quantity and type of crimes. The effectiveness and usefulness of the proposed methodologies have been demonstrated with a comprehensive set of quantitative and qualitative analyses, as well as case studies performed by domain experts involving real data from different-sized cities. The experiments show the capability of our approaches in identifying different crime-related phenomena.
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Jayaweera, Isuru, Chamath Sajeewa, Sampath Liyanage, Tharindu Wijewardane, Indika Perera, and Adeesha Wijayasiri. "Crime analytics: Analysis of crimes through newspaper articles." In 2015 Moratuwa Engineering Research Conference (MERCon). IEEE, 2015. http://dx.doi.org/10.1109/mercon.2015.7112359.

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Hacin, Rok. "Kriminaliteta v občinah ob schengenski meji." In Varnost v ruralnih in urbanih okoljih: konferenčni zbornik. Univerzitetna založba Univerze v Mariboru, 2020. http://dx.doi.org/10.18690/978-961-286-404-011.

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The paper focuses on the crime analysis in the 32 municipalities at the Schengen border in the period 2010–2019. The results of the analysis of police crime statistics show that crimes against property present the most frequent form of crime in municipalities at the Schengen border, followed by forgery of documents, threat, the prohibited crossing of the state border or territory, counterfeiting or destruction of business documents, and minor bodily injury. In the analysed period, the number of crimes against public order and peace increased significantly (especially number of crimes of the prohibited crossing of the state border or territory), which can be [at least partially] attributed to the migrant crisis in recent years. In the period 2010–2019, these forms of crime increased mainly in the following municipalities Brežice, Cirkulane, Ilirska Bistrica, Krško, Podlehnik, Razkrižje and Šentjernej. Overall, the number of crimes, similarly as elsewhere in Slovenia, increases with the size of the municipality and the number of population in the municipality.
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Pratibha, Akanksha Gahalot, Uprant, Suraina Dhiman, and Lokesh Chouhan. "Crime Prediction and Analysis." In 2020 2nd International Conference on Data, Engineering and Applications (IDEA). IEEE, 2020. http://dx.doi.org/10.1109/idea49133.2020.9170731.

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Fischer, Robert, and Claus Vielhauer. "Digital crime scene analysis." In the 2nd ACM workshop. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2600918.2600930.

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Fotios, S., C. J. Robbins, and S. Farrall. "INVESTIGATING LIGHT AND CRIME USING AMBIENT LIGHT LEVEL." In CIE 2021 Conference. International Commission on Illumination, CIE, 2021. http://dx.doi.org/10.25039/x48.2021.op31.

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A recent study investigated the influence of lighting on crime by considering the effect of change in ambient light level on crimes recorded in three US cities for the ten-year period 2010 to 2019. The results suggested a significant increase in robbery after dark, but did not suggest significant change in for any other type of crime. The current study was conducted to validate this by considering crimes recorded in three different US cities. This analysis confirmed the statistically significant increase in robbery after dark. These data do not suggest that change in ambient light level has a practically relevant effect on overall crime counts: in other words, the potential benefit of lighting for crime reduction is limited.
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P, Suganthi, Aiswarya S M, Kaviyanjali M, and Sushmasri Chitturi. "Evaluating Crime Type And Crime Pattern Analysis Using Machine Learning." In 2024 IEEE 9th International Conference for Convergence in Technology (I2CT). IEEE, 2024. http://dx.doi.org/10.1109/i2ct61223.2024.10543291.

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Kilic, Sedat, and Mihran Tuceryan. "Crime Detection from Pre-crime Video Analysis with Augmented Pose and Emotion Information." In 2024 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI). IEEE, 2024. http://dx.doi.org/10.1109/ssiai59505.2024.10508694.

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Oatley, Giles, and Tom Crick. "Measuring UK crime gangs." In 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2014. http://dx.doi.org/10.1109/asonam.2014.6921592.

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Reports on the topic "Crime analysis"

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Ajzenman, Nicolás, and Laura Jaitman. Crime Concentration and Hot Spot Dynamics in Latin America. Inter-American Development Bank, June 2016. http://dx.doi.org/10.18235/0011745.

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Latin America and the Caribbean is the most violent region in the world, with an annual homicide rate of more than 20 per 100,000 population and with an increasing trend. Yet most evidence of crime concentration, geo-temporal patterns, and event dependence comes from cities in high-income countries. Understanding crime patterns in the region and how they compare to those in high-income countries is of first-order importance to formulate crime reduction policies. This paper is the first to analyze crime patterns of cities in five Latin American countries. Using micro-geographic units of analysis, the paper finds, first, that crime in Latin America is highly concentrated in a small proportion of blocks: 50 percent of crimes are concentrated in 3 to 7.5 percent of street segments, and 25 percent of crimes are concentrated in 0.5 to 2.9 percent of street segments. This validates Weisburd's "law of crime concentration at place" (Weisburd, 2105). These figures are fairly constant over time but sensitive to major police reforms. The second finding is that hot spots of crime are not always persistent. Crime is constantly prevalent in certain areas, but in other areas hot spots either appear or disappear, suggesting a possible rational adaptation from criminals to police actions that cause crime displacement in the medium run to other areas. Finally, the paper finds a significant pattern of repeated crime victimization in location and time for property crimes. There are striking similarities with the developed world in crime concentration, although crime levels are much higher and usually increasing. There are also some differences in terms of the persistence of hot spots that pose interesting policy implications and avenues for future research.
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Markowitz, Sara. An Economic Analysis of Alcohol, Drugs, and Violent Crime in the National Crime Victimization Survey. Cambridge, MA: National Bureau of Economic Research, October 2000. http://dx.doi.org/10.3386/w7982.

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Russell, Kortney. Crime Risk near Reported Homeless Encampments: a Spatial Analysis. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.7435.

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Shekhar, Shashi, Pradeep Mohan, Dev Oliver, and Xun Zhou. Crime Pattern Analysis: A Spatial Frequent Pattern Mining Approach. Fort Belvoir, VA: Defense Technical Information Center, May 2012. http://dx.doi.org/10.21236/ada561517.

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Keefer, Philip, Dino Caprirolo, Heather Sutton, José Antonio Mejía-Guerra, Ted Leggett, Iván Torre, James Andrew Lewis, Laura Jaitman, and Rogelio Granguillhome Ochoa. The Costs of Crime and Violence: New Evidence and Insights in Latin America and the Caribbean (Executive Summary). Inter-American Development Bank, February 2017. http://dx.doi.org/10.18235/0006383.

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This publication is the first to provide a comprehensive, systematic and rigorous analysis of the costs of crime in Latin America and the Caribbean. The main challenges in the region are addressed: the social cost of homicides, private and public spending on security, the penitentiary crisis, violence against women, organized crime and cybercrime. The volume estimates that the direct cost of crime for 17 LAC countries in 2010-2014 is, on average, 3.5 percent of the region's GDP--twice as much as in the developed world. This volume also provides a detailed analysis of the costs of crime in Brazil by state, as well as an examination of the geographical distribution and drivers of crime in the most dangerous subregions: the Northern Triangle in Central America and the Caribbean. The situation in terms of violence against women and cybercrime is assessed: the region is lagging behind to confront these new and old crimes. The complete version of this publication is available at https://publications.iadb.org/handle/11319/8133.
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Krueger, Alan, and Jorn-Steffen Pischke. A Statistical Analysis of Crime Against Foreigners in Unified Germany. Cambridge, MA: National Bureau of Economic Research, March 1996. http://dx.doi.org/10.3386/w5485.

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Bailey, Corin. Crime and Violence in Barbados: IDB Series on Crime and Violence in the Caribbean. Inter-American Development Bank, June 2016. http://dx.doi.org/10.18235/0009299.

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This report is part of the Inter-American Development Bank's Technical Note Series on Crime and Violence in the Caribbean. The overall aim is to establish a baseline of the crime-prevention arena against which progress can be assessed. The report compiles available data from multiple sourcesto provide a diagnostic of the size, characteristics, and changing nature of the problem in Barbados in recent years. In addition, the report provides a survey of the various crime-prevention and suppression policies, programs, and projects adopted by the government, private companies, and nongovernmental organisations. In performing the aforementioned tasks, the report (a) offers an assessment of the data collection, analysis, and crime response capabilities in Barbados; and (b) makes suggestions about the most effective plans for corrective action.
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Harriot, Anthony D., and Marlyn Jones. Crime and Violence in Jamaica: IDB Series on Crime and Violence in the Caribbean. Inter-American Development Bank, June 2016. http://dx.doi.org/10.18235/0009298.

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This report is part of an IDB technical note series on crime and violence in the Caribbean. The overall aim is to establish a baseline of the crime prevention arena against which progress can be assessed. The report compiles the available data from multiple sources in order to provide a diagnosis of the size, characteristics, and changing nature of the crime problem in Jamaica over the last 10 years. In addition, the report provides a survey of the various crime prevention and suppression policies, programmes, and projects adopted by government, private organizations, and non-governmental organizations in recent years. In performing the above-mentioned tasks, the report offers an assessment of the data collection, analysis, and crime response capabilities in Jamaica, and makes suggestions regarding the most effective way forward.
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Sutton, Heather. Crime and Violence in The Bahamas: IDB Series on Crime and Violence in the Caribbean. Inter-American Development Bank, June 2016. http://dx.doi.org/10.18235/0009296.

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This report is part of an IDB technical note series on crime and violence in the Caribbean. The overall aim is to establish a baseline in the crime prevention arena against which progress can be assessed. The report compiles the available data from multiple sources in order to provide a diagnosis of the size, characteristics, and changing nature of the problem of crime and violence in The Bahamas. In addition, the report provides a survey of the various crime prevention and suppression policies, programs and projects adopted by government and private and nongovernmental organizations in recent years. In performing the above-mentioned tasks, the report offers an assessment of the data collection, analysis, and crime response capabilities in The Bahamas, and makes suggestions about the most effective way forward.
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Seepersad, Randy. Crime and Violence in Trinidad and Tobago: IDB Series on Crime and Violence in the Caribbean. Inter-American Development Bank, June 2016. http://dx.doi.org/10.18235/0009297.

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This report is part of an IDB Technical Note series on crime and violence in the Caribbean. The overall aim is to establish a baseline of the crime prevention arena against which progress can be assessed. The report compiles the available data from multiple sources in order to provide a diagnosis of the size, characteristics, and changing nature of the problem in Trinidad and Tobago. In addition, the report provides a survey of the various crime prevention and suppression policies, programmes, and projects adopted by government, private and non-governmental organisations in recent years. In performing the above-mentioned tasks, the report offers an assessment of the data collection, analysis, and crime response capabilities in Trinidad and Tobago, and makes suggestions about the most effective way forward.
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