CRIME PREDICTION USING SOCIAL SENTIMENT AND SOCIO-FACTOR

Year 2018, Volume: 60 Issue: 1, 11 - 20, 31.07.2018

Sakirin Tam Ö. Özgür Tanrıöver

Abstract

Crime prediction becomes very important trend and a
key technique in crime analysis to identify the optimal patrol strategy for
police department. Many researchers have found number of techniques and
solutions to analyze crime, using data mining techniques. These studies can
help to speed up and computerize the process of crime analysis processes.  However, the pattern of crime is flexible, it
always changes and grows. With social media, user posts and discusses event
publicly. These textual data of every user has contextual information of user’s
daily activities. These posts generate unstructured data that can be used for
data prediction. As shown by previous research, twitter sentiment enable to
predict crime in Chicago, United States. However, existed model on crime
prediction was incorporating the use of socio factors. Therefore, the study
aims to model crime prediction using social media content with additional
socio-factors. The research approach is consisted of a combination of sentiment
analysis from Twitter and social-factors with Kernel Density Estimation.
Lexicon-base methods will be applied for sentiment analysis, and the model
evaluation is measured with the help of logistic regression. 

Keywords

Crime prediction, Data mining, Social media, Sentiment analysis, Socio-Factor

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