Spatio-temporal Crime Analysis and Forecasting on Twitter Data Using Machine Learning Algorithms-Reference-Cited by-同舟云学术

Spatio-temporal Crime Analysis and Forecasting on Twitter Data Using Machine Learning Algorithms

Published:2023-05-06 Issue:4 Volume:4 Page:
ISSN:2661-8907
Container-title:SN Computer Science
language:en
Short-container-title:SN COMPUT. SCI.

Author:

Vivek Meghashyam,Prathap Boppuru Rudra^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Networks and Communications,Computer Graphics and Computer-Aided Design,Computational Theory and Mathematics,Artificial Intelligence,General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s42979-023-01816-y.pdf

Reference24 articles.

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2. Ohyama T, et al. Investigating crime harm index in the low and downward crime contexts: a spatio-temporal analysis of the Japanese Crime Harm Index. Cities. 2022;130:103922.

3. Catlett C, et al. Spatio-temporal crime predictions in smart cities: a data-driven approach and experiments. Pervas Mob Comput. 2019;53:62–74.

4. Hu Y, et al. A spatio-temporal kernel density estimation framework for predictive crime hotspot mapping and evaluation. Appl Geogr. 2018;99:89–97.

5. Rummens A, Hardyns W, Pauwels L. The use of predictive analysis in spatiotemporal crime forecasting: building and testing a model in an urban context. Appl Geogr. 2017;86:255–61.

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