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Crime Detection and Prevention using Social Network Analysis

by Shikhar Gupta, Sanjeev Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 126 - Number 6
Year of Publication: 2015
Authors: Shikhar Gupta, Sanjeev Kumar

Shikhar Gupta, Sanjeev Kumar . Crime Detection and Prevention using Social Network Analysis. International Journal of Computer Applications. 126, 6 ( September 2015), 14-19. DOI=10.5120/ijca2015906065

@article{ 10.5120/ijca2015906065,
author = { Shikhar Gupta, Sanjeev Kumar },
title = { Crime Detection and Prevention using Social Network Analysis },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 126 },
number = { 6 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 14-19 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2015906065 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T23:16:43.855753+05:30
%A Shikhar Gupta
%A Sanjeev Kumar
%T Crime Detection and Prevention using Social Network Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 126
%N 6
%P 14-19
%D 2015
%I Foundation of Computer Science (FCS), NY, USA

A society is built of individuals and group of individuals make organization. These individuals or organizations are also called as nodes. A structure that consist these nodes and relation between these nodes is known as social networking. We all are surrounded by networks and plays an important role of individual unit in a network of different kinds of social relationships, biological systems. In current scenation social networking and blogs are the most popular kind of online activities. Usage of social networks are much more than personal emails. Facebook, Twitter & LinkedIn are some of the well-known examples of Social networking. It is the analysis of how social groups communicate & connect to each other & affect important features. Social network analysis is not just analysis of an individual, but it is the study of group of individual and relation between them. Social Network Analysis is current emerging area of importance in finance, politics, defense and security. Prediction of missing links & links that can occur in future between notes in social network is an attention holding topic. It is of interest that Fuzzy system analysis can make more significant & correct predictions. There are many methods to depict knowledge in the field of soft computing. But the most common way to portray the human understanding is with the help of natural language expression also called fuzzy rule-based system. With the help of this rule based form if we aware of information, then we can drive another information called as conslusion. Fuzzy system is used to identify the trait of an individual. We take five different characteristics like economical status, family background, educational level, alcoholic &drug addict and criminal history. All of these Characteristics of an individual are mapped with the help of fuzzification & de-fuzzification techniques to obtain a de-fuzzification value. These values help to identify the criminal phycology of a person. Each value is then assigned a colour. Colours are in given order starting from highest criminal level to lowest: Dark Red, Red, Light Red, Orange, Yellow, White, and Green. When all the node gets its appropriate colour, we analyse the interaction between the nodes and reassign a colour to a node if its activities in not appropriate according to the characteristic values provided by the user or if a person is interaction with someone who is already placed in some other category. For this re-analysis we again use fuzzy system techniques.

  1. A.L. Barabasi, N. Gulbahce, J. Loscalzo, “Network medicine: a network-based approach to human disease”, Nature Reviews Genetics, 12(1), 56–68, 2011.
  2. A.L. Barabasi, R. Albert, “Emergence of Scaling in Random Networks”, Science 286 (1999) 509, 1999.
  3. C. Zhou, A. E. Motter, and J. Kurths, “University in the Synchronization of Weighted Random Networks”. Phys. Rev. Lett. 96, 034101(2006).
  4. D.J. Watts, S.H. Strogatz, Nature 393 (1998) 440.
  5. D.J. Watts, Small Worlds: The Dynamics of Networks between Order and Randomness, Princeton University Press, Princeton, NJ, 1999.
  6. Maarten van Steen, “An Introduction to Graph Theory and Complex Network”, 2010.
  7. R. Cohen, S. Halvin, “Scall-Free networks are ultrasmall”. Phys. Rev. Lett90 (5): 058701, 2003.
  8. S. Boccaletti, V. Latora, Y. Moreno, M. Chavez, D.U. Hwang, “Complex networks: Structure and dynamics”, journal of ELSEVIER, 2005.
  9. S. Rajasekaran, G. A. Vijayalakshmi Pai, 2009. “Neural Network, Fuzzy Logic, and Genetic Algorithms Synthesis and Applications”. PHI Learning private Ltd. , Twelfth Edition.
  10. T.J. Ross, “Fuzzy Logic with Engineering Applications”, WILEY publication, Third edition, 2010.
  11. Wasserman, Stanley and Katherine Faust, “Social Network Analysis: Methods and Applications”, Cambridge University Press, 1994.
  12. Y. Kuramoto, “Self-entrainment of a population of coupled nonlinear oscillators”, Lect. Notes Phys, 30, 420 (1975).
  13. Yamir Moreno, “Complex Network Modeling: A New Approach to Neurosciences”Springer Series in Computational Neuroscience Volume 2, 2009, pp 241-263.
Index Terms

Computer Science
Information Sciences


Social network analysis Crime detection Fuzzy rules Network models Synchronization process.