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http://dx.doi.org/10.3745/KTCCS.2016.5.9.229

An Analysis of Relationship Between Word Frequency in Social Network Service Data and Crime Occurences  

Kim, Yong-Woo (가톨릭대학교 디지털미디어학과)
Kang, Hang-Bong (가톨릭대학교 디지털미디어학부)
Publication Information
KIPS Transactions on Computer and Communication Systems / v.5, no.9, 2016 , pp. 229-236 More about this Journal
Abstract
In the past, crime prediction methods utilized previous records to accurately predict crime occurrences. Yet these crime prediction models had difficulty in updating immense data. To enhance the crime prediction methods, some approaches used social network service (SNS) data in crime prediction studies, but the relationship between SNS data and crime records has not been studied thoroughly. Hence, in this paper, we analyze the relationship between SNS data and criminal occurrences in the perspective of crime prediction. Using Latent Dirichlet Allocation (LDA), we extract tweets that included any words regarding criminal occurrences and analyze the changes in tweet frequency according to the crime records. We then calculate the number of tweets including crime related words and investigate accordingly depending on crime occurrences. Our experimental results demonstrate that there is a difference in crime related tweet occurrences when criminal activity occurs. Moreover, our results show that SNS data analysis will be helpful in crime prediction model as there are certain patterns in tweet occurrences before and after the crime.
Keywords
Social Network Service; Crime Record; Latent Dirichlet Allocation; Tweet Frequency;
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Times Cited By KSCI : 3  (Citation Analysis)
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