Title :
Predicting Next Location of Twitter Users for Surveillance
Author :
Gunduz, Sedef ; Yavanoglu, Uraz ; Sagiroglu, Seref
Author_Institution :
Dept. of Comput. Eng., Gazi Univ., Ankara, Turkey
Abstract :
In this study a novel approach that uses location based social networks for next location prediction in the field of technical surveillance and digital forensics is proposed. With the help of proposed methodology, search area for the potential criminals will be narrowed so that the spent time, money and effort by the law enforcement officers will be minimized. After collecting enough past location information for Foursquare users, the whole data is trained by means of Artificial Neural Networks. After training process, predicting the next location of the wanted personis carried out. Prediction process is made region-based, so it is tried to predict the region of the potential criminals´ next geographical location. The experimental results have shown that the proposed approach and developed system might achieve the prediction goal with only 3% error rate, and proposed methodology can be used by law enforcement officers for forensic surveillance and similar criminal acts.
Keywords :
Internet; digital forensics; law; neural nets; social networking (online); video surveillance; artificial neural networks; digital forensics; foursquare users; geographical location; law enforcement officers; predicting next location; social networks; technical surveillance; twitter users; Artificial neural networks; Law enforcement; Prediction algorithms; Predictive models; Social network services; Surveillance; Training; Digital Forensics; Information Security; Location Based Social Networks; Location Prediction; Social Networks; Technical Surveillance;
Conference_Titel :
Machine Learning and Applications (ICMLA), 2013 12th International Conference on
Conference_Location :
Miami, FL
DOI :
10.1109/ICMLA.2013.134