Repo for the UCL 3rd year UG module Advanced Crime Analysis (Data Science)
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This is the companion website for the 2018-2019 module for 3rd year undergraduate students of the BSc in Crime Science at UCL.


The module handbook provides you with all information around assessment, learning outcomes, timetables, and a general overview of the module. Use the module handbook as your go-to guide throughout the module.

Week 1

Suggested reading:

  • Williams, M. L., Burnap, P., & Sloan, L. (2017). Crime Sensing With Big Data: The Affordances and Limitations of Using Open-source Communications to Estimate Crime Patterns. The British Journal of Criminology, 57(2), 320–340.


Week 2

Required reading/preparation:

Suggested reading:

  • Solymosi, R., Bowers, K. J., & Fujiyama, T. (2018). Crowdsourcing Subjective Perceptions of Neighbourhood Disorder: Interpreting Bias in Open Data. The British Journal of Criminology, 58(4), 944–967.
  • Founta, A.-M., Djouvas, C., Chatzakou, D., Leontiadis, I., Blackburn, J., Stringhini, G., … Kourtellis, N. (2018). Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior. ArXiv:1802.00393 [Cs]. Retrieved from

Week 3

  • Lecture 3: Webscraping with R (slides), pdf
  • Homework: -

Required reading:

Suggested reading:

  • ElSherief, M., Kulkarni, V., Nguyen, D., Wang, W. Y., & Belding, E. (2018). Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media. ArXiv:1804.04257 [Cs]. Retrieved from

Tutorial: Webscraping and APIs in R

Module convenor and author: Bennett Kleinberg (

Department of Security and Crime Science, UCL