DocumentCode
1828908
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
Volume
2
fYear
2013
fDate
4-7 Dec. 2013
Firstpage
267
Lastpage
273
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications (ICMLA), 2013 12th International Conference on
Conference_Location
Miami, FL
Type
conf
DOI
10.1109/ICMLA.2013.134
Filename
6786119
Link To Document