The use of social media data to gain insights into public phenomena is a potentially powerful tool. We present the use of social media data analysis, connected with crime and public safety incidents, to better understand reoccurring topics and potentially feed into an automated incident detection application. We collected a size-able dataset of Twitter posts (more than 60,000) over a 3 month period by monitoring crime and public safety related keywords linked to accounts. By splitting the data into two categories we are able to extract topics as well as compare and contrast how monitoring official crime and public safety accounts differs from monitoring individuals and organisations that may not be part of that group. Finally we discuss a prototype application, which uses social media data as well as locations to calculate metrics using potential crime and public safety related incidents.
Reference:
Marivate, VN. 2015. Extracting South African safety and security incident patterns from social media. In: Proceedings of the 2015 Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference, 26-27 November, Port Elizabeth, South Africa
Marivate, V. N. (2015). Extracting South African safety and security incident patterns from social media. IEEE Xplore. http://hdl.handle.net/10204/8383
Marivate, Vukosi N. "Extracting South African safety and security incident patterns from social media." (2015): http://hdl.handle.net/10204/8383
Marivate VN, Extracting South African safety and security incident patterns from social media; IEEE Xplore; 2015. http://hdl.handle.net/10204/8383 .
Proceedings of the 2015 Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference, 26-27 November, Port Elizabeth, South Africa. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website