Integration of social media in spatial crime analysis and prediction models for events
Document Type
Conference Proceeding
Publication Date
1-1-2017
Abstract
The last decade has been the most productive in respect to social media data exploration and possible uses in crime prediction. This area is thus a rapidly evolving and growing field. This PhD research aims to find and evaluate spatial relationships between crime occurrences and nearby social media activity for events areas and estimating the possible influence of this activity for crime prediction models. Overall, the thesis will focus on geospatial crime prediction concerning planned and emerging events through the exploration of social media data, and other information including demographic, economic and safety risk factors. The thesis will utilize methods and tools from various fields including: social media text mining and classification from machine learning; spatial statistics together with forecasting models from crime prediction. Outcomes will be a valuable basis for defining new research areas, helping to understand further spatial crime analysis and prediction models that include secondary data sources, such as social media, on the basis of event exploration.
Publication Source (Journal or Book title)
CEUR Workshop Proceedings
Number
541
Recommended Citation
Ristea, A., & Leitner, M. (2017). Integration of social media in spatial crime analysis and prediction models for events. CEUR Workshop Proceedings, 2088 Retrieved from https://repository.lsu.edu/geoanth_pubs/541