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Smart city article details
| Title | Crime Prediction Using Support Vector Machine And Extracted Twitter Features |
|---|---|
| ID_Doc | 16545 |
| Authors | Rojo J.F.S.; Bocanegra L.A.F.; Vega J.F.B.; Gomez N.G. |
| Year | 2023 |
| Published | 2023 IEEE Colombian Conference on Communications and Computing, COLCOM 2023 - Proceedings |
| DOI | http://dx.doi.org/10.1109/COLCOM59909.2023.10334281 |
| Abstract | Citizen security in smart cities is a historical prob-lem that is addressed from several fronts. One of them is the implementation of intelligent solutions based on computational intelligence techniques that allow to develop preventive and/or reactive strategies to improve the life quality of citizens. This article presents a strategy that allows cities to predict criminal acts in specific spaces and times based on citizen participation through the Twitter social network. The proposed method consists of using a natural language processing model to extract features of the tweets made in the space and time of interest in order to predict if a criminal act will be committed in a later time window. The proposed method is able to predict future time windows where criminal acts will potentially be committed with a percentage of 87 % with a resulting accuracy of 77 %. © 2023 IEEE. |
| Author Keywords | Citizen security; Crime prediction; Natural language processing; Support vector machine |
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