A Framework for Mapping Crime Data on Sociological Hypothesis

Data is increasing every second now a days. Interesting facts about the societies can be extracted by converting the data into useful information as user generated content helps to reveal the audience’s perception on different social aspects. Crime is a serious concern all over the world because it affects humans and also the environment surrounding them. Social criminal theories help to identify different aspects of humans that cause the person to commit crime. There is a need to identify the hidden patterns and also the relationship between the data and social theories. In this paper, a framework is proposed that maps the crime data on established social criminal theories. A total of 100 cases have been mapped to check the correctness of the solution. This solution can have great impact on the society to counter the problems of increasing crime and understand the reasons of crime, and also help to take the remedial actions. In this paper, we have considered only social criminal theories, in future we will extend this research by elaborating more criminal theories.

[1]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[2]  Gang Wang,et al.  Crime data mining: a general framework and some examples , 2004, Computer.

[3]  P. Thongtae,et al.  An Analysis of Data Mining Applications in Crime Domain , 2008, 2008 IEEE 8th International Conference on Computer and Information Technology Workshops.

[4]  Donna R. Tabangin,et al.  Investigating Crime Hotspot Places and their Implication to Urban Environmental Design: A Geographic Visualization and Data Mining Approach , 2008 .

[5]  Wei Ding,et al.  Crime Forecasting Using Data Mining Techniques , 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.

[6]  Mohammad Reza Keyvanpour,et al.  Detecting and investigating crime by means of data mining: a general crime matching framework , 2011, WCIT.

[7]  Kadhim B. S. Aljanabi A Proposed Framework for Analyzing Crime Data Set Using Decision Tree and Simple K-Means Mining Algorithms , 2011 .

[8]  C. Bail The cultural environment: measuring culture with big data , 2014, Theory and Society.

[9]  Shiju Sathyadevan,et al.  Crime analysis and prediction using data mining , 2014, 2014 First International Conference on Networks & Soft Computing (ICNSC2014).

[10]  Huan Liu,et al.  Mining social media with social theories: a survey , 2014, SKDD.

[11]  Geeta Sikka,et al.  An Optimized Approach for Density Based Spatial Clustering Application with Noise , 2014 .

[12]  S. Lee,et al.  Ubiquitous Crime Prevention System (UCPS) for a Safer City , 2014 .

[13]  Alexander Halavais Bigger sociological imaginations: framing big social data theory and methods , 2015 .

[14]  Natarajan Meghanathan,et al.  USING MACHINE LEARNING ALGORITHMS TO ANALYZE CRIME DATA , 2015 .

[15]  K. L. Man,et al.  Social network analysis using big data , 2016, IMECS 2016.

[16]  Yang Jie,et al.  Discovering Gangs of Criminals Using Data Fusion With Social Networks , 2016 .

[17]  Brian Hilton,et al.  Big Social Data and GIS: Visualize Predictive Crime , 2016, AMCIS.

[18]  M. Williams,et al.  Crime sensing with big data: the affordances and limitations of using open source communications to estimate crime patterns , 2016 .

[19]  Vernon Gayle,et al.  The role of administrative data in the big data revolution in social science research. , 2016, Social science research.

[20]  Daniel A. McFarland,et al.  Sociology in the Era of Big Data: The Ascent of Forensic Social Science , 2015, The American Sociologist.

[21]  Jiliang Tang,et al.  Crime in Urban Areas:: A Data Mining Perspective , 2018, SKDD.