1.
Miller, A. M. Review of R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham and Garrett Grolemund. ACM SIGACT News 48, 14–19 (2017).
2.
Williams, M. L., Burnap, P. & Sloan, L. Crime Sensing with Big Data: The Affordances and Limitations of using Open Source Communications to Estimate Crime Patterns. British Journal of Criminology (2016) doi:10.1093/bjc/azw031.
3.
Chen, X., Cho, Y. & Jang, S. Y. Crime prediction using Twitter sentiment and weather. in 2015 Systems and Information Engineering Design Symposium 63–68 (IEEE, 2015). doi:10.1109/SIEDS.2015.7117012.
4.
Wang, M. & Gerber, M. S. Using Twitter for Next-Place Prediction, with an Application to Crime Prediction. in 2015 IEEE Symposium Series on Computational Intelligence 941–948 (IEEE, 2015). doi:10.1109/SSCI.2015.138.
5.
Ristea, A., Langford, C. & Leitner, M. Relationships between crime and Twitter activity around stadiums. in 2017 25th International Conference on Geoinformatics 1–5 (IEEE, 2017). doi:10.1109/GEOINFORMATICS.2017.8090933.
6.
Kostakos, P. Public perceptions on organised crime, Mafia, and Terrorism: A big data analysis based on Twitter and Google Trends. International Journal of Cyber Criminology 12, 282–299.
7.
Almehmadi, A., Joudaki, Z. & Jalali, R. Language usage on Twitter predicts crime rates. in Proceedings of the 10th International Conference on Security of Information and Networks  - SIN ’17 307–310 (ACM Press, 2017). doi:10.1145/3136825.3136854.
8.
Pfeffer, J., Mayer, K. & Morstatter, F. Tampering with Twitter’s Sample API. EPJ Data Science 7, (2018).
9.
Solymosi, R., Bowers, K. J. & Fujiyama, T. Crowdsourcing Subjective Perceptions of Neighbourhood Disorder: Interpreting Bias in Open Data. The British Journal of Criminology 58, 944–967 (2018).
10.
Founta, Antigoni-Maria. Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior.
11.
HTML basics | MDN. https://developer.mozilla.org/en-US/docs/Learn/Getting_started_with_the_web/HTML_basics.
12.
R Web Scraping Tutorial with rvest (article) - DataCamp. https://www.datacamp.com/community/tutorials/r-web-scraping-rvest.
13.
Web scraping tutorial in R – Towards Data Science. https://towardsdatascience.com/web-scraping-tutorial-in-r-5e71fd107f32.
14.
Learn To Create Your Own Datasets — Web Scraping in R. https://towardsdatascience.com/learn-to-create-your-own-datasets-web-scraping-in-r-f934a31748a5.
15.
Hadley Wickham. Easily Harvest (Scrape) Web Pages [R package rvest version 0.3.2].
16.
ElSherief, Mai. Hate Lingo: A Target-based Linguistic Analysis of Hate Speech in Social Media. (2018).
17.
14 Strings | R for Data Science. https://r4ds.had.co.nz/strings.html.
18.
Replication of Chapter 5 of <em>Quantitative Social Science: An Introduction</em> • quanteda. https://quanteda.io/articles/pkgdown/replication/qss.html.
19.
Example: textual data visualization • quanteda. https://quanteda.io/articles/pkgdown/examples/plotting.html.
20.
Kleinberg, Bennett. Identifying the sentiment styles of YouTube’s vloggers.
21.
Pérez-Rosas, Verónica. Automatic Detection of Fake News.
22.
Kuhn, M. & Johnson, K. Applied predictive modeling. (Springer, 2013).
23.
Hastie, T., Tibshirani, R. & Friedman, J. H. The elements of statistical learning: data mining, inference, and prediction. (Springer Verlag, 2009).
24.
An Introduction to Machine Learning with R. https://lgatto.github.io/IntroMachineLearningWithR/unsupervised-learning.html.
25.
R: Unsupervised Learning | DataCamp. https://www.datacamp.com/courses/unsupervised-learning-in-r.
26.
Coveney, P. V., Dougherty, E. R. & Highfield, R. R. Big data need big theory too. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 374, (2016).
27.
Quijano-Sánchez, L., Liberatore, F., Camacho-Collados, J. & Camacho-Collados, M. Applying automatic text-based detection of deceptive language to police reports: Extracting behavioral patterns from a multi-step classification model to understand how we lie to the police. Knowledge-Based Systems 149, 155–168 (2018).
28.
Kadar, C. & Pletikosa, I. Mining large-scale human mobility data for long-term crime prediction. EPJ Data Science 7, (2018).
29.
Burnap, P. & Williams, M. L. Us and them: identifying cyber hate on Twitter across multiple protected characteristics. EPJ Data Science 5, (2016).