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This list relates to the academic year Academic Year 2018/19 which ended on 05/07/2019
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  1. Overview 1 item
  2. week 1 1 item
  3. week 2 - Articles referenced in the lecture 5 items
    1. Crime prediction using Twitter sentiment and weather - Xinyu Chen, Youngwoon Cho, Suk Young Jang 2015-4-24

      Article Optional

    2. Relationships between crime and Twitter activity around stadiums - Alina Ristea, Chad Langford, Michael Leitner 2017-8

      Article Optional

    3. Language usage on Twitter predicts crime rates - Abdulaziz Almehmadi, Zeinab Joudaki, Roozbeh Jalali 2017

      Article Optional

  4. week 2 - Required reading/preparation 1 item
    1. Tampering with Twitter’s Sample API - Jürgen Pfeffer, Katja Mayer, Fred Morstatter 12/2018

      Article 

  5. week 2 - Suggested reading 2 items
  6. week 3 - Required reading 5 items
  7. week 3 - Suggested reading 1 item
  8. week 4 - Required reading 1 item
  9. week 4 - Suggested reading 2 items
  10. week 5 - Required reading 2 items
  11. week 6 - Required reading 1 item
    1. Applied predictive modeling - Max Kuhn, Kjell Johnson c2013

      Book Essential Chapters: "Introduction" and "A Short Tour of the Predictive Modeling Process"

  12. week 6 - Suggested reading 1 item
    1. The elements of statistical learning: data mining, inference, and prediction - Trevor Hastie, Robert Tibshirani, J. H. Friedman c2009

      Book Recommended Chapters: "Overview of Supervised Learning" and "Linear Methods for Classification"

  13. week 7 - Required reading 1 item
  14. week 7 - Recommended material 1 item
  15. week 8 - Required reading 1 item
    1. Big data need big theory too - Peter V. Coveney, Edward R. Dougherty, Roger R. Highfield 13/11/2016

      Article 

  16. week 8 - Recommended reading 3 items
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