Master's Thesis from the year 2015 in the subject Engineering - Computer Engineering, grade: 7.8, Indian Institute of Engineering Science and Technology, Shibpur (IBM INDIA PRIVATE LIMITED), language: English, abstract: In this 21st century the technological advancement in computational areas has already put its footsteps in every fields of science, sociology, health, business and in many others. Now the people are connected across the world using internets and more precisely we can say that the communication is done freely through social networks. From that point of view researchers try to analyze the social networks for the betterment of different domains or trying to create something useful using the social networks. Now we will try to use this ground to help the victims and use their information's to stop the upcoming criminal activities by analyzing those informations. It will help the common people to know how and where antisocial activities are being held. Here WEKA which implements data mining algorithms is a state-of-the-art facility for developing machine learning (ML) techniques and their application to real-world data mining problems will be used to analyze the collected data. After data collection, based on different types of criminal incidents some communities will be formed. These communities are helpful to detect real world gang or group activities related to crimes. Recommendation in social media is useful concept to aware people and fight against antisocial activities. Model based collaborative filtering which is a type of recommendation in social media will be used to find common criminal behavior towards different criminal activities. Concepts of herd behavior and collective behavior will also be used to find victims adoption of behaviors in different timestamps from initial timestamp.
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