Clustering Crimes Related Twitter Posts using WordNet and Agglomerative Algorithm

Abstract

Abstract: Crime is a major problem faced today by society. Crimes have affected the quality of life and economic growth badly. We can identify the crime patterns and predict the crimes by detecting and analyzing the historical data. We can use social media like twitter to detect crimes related activities. Because Twitter users sometimes convey messages related to his or her surrounding environment via twitter. In this paper, we proposed a machine learning approach to cluster the crime-related twitter post based on the crime category. The empirical study of our prototyping system has proved the effectiveness of our proposed clustering approach. Keywords: Clustering, WordNet, Agglomerative algorithm, SVM