Crime Suspect Profiling (CSP) for Forensic Investigation on Smartphone

Recently, crime cases have been highly reported due to the increased of the utilization of technology. The development of system aims to identify the probable suspects based on social network messages. The study focuses on certain features extracted from the content of social media text messages. There were four features identified namely location, time, object and person. These four features help to manage the system based on specified crime messages. The implementation of features for crime suspect profiling (CSP) utilizes text mining through named entity recognition to identify the word or phrase for particular features. In this study, the suspect measure was obtained through the integrated similarity. Results obtained from the experiments conducted have revealed the similarity value that reflects the possibility of a contact as a suspect to the crime. The results of this study affirmed that the suspect profiling through the messages content is promising to identify the suspects.