4TU-CSS
Material for a Computational Social Science (CSS) Workshop hosted by the four Dutch technical universities.
Project maintained by vtraag Hosted on GitHub Pages — Theme by mattgraham
4TU Computational Social Science Seminar
7 April 2017 @ University of Twente
With increasing amounts of data the social sciences have the opportunity to become more computationally oriented, bringing together elements of machine learning and data science with substantive social theories. We will provide a brief introduction to the core of the computational social science. The main focus in this workshop is on two key elements of this new field: natural language processing (NLP) and social networks. We will take a hands-on approach, with interactive lectures that combine theoretical explanations with actual coding. In the group assignments, we will stimulate an integrated approach to both NLP and network analysis.
Programme
| Time | Topic |
|---|---|
| 10:00 - 10:30 | Computational Social Science introduction |
| 10:30 - 12:30 | Natural Language Processing (NLP) lab The first part will focus on applying NLP tools. Topics that will be discussed include sentiment analysis, named entity recognition, part-of-speech tagging and feature representation. The second part will focus on NLP to analyze and model social dynamics. We will discuss computational approaches to analyze language & social identity (gender, age, location) and language in interaction (e.g., social relationships, dynamics in online communities). |
| 12:30 - 13:30 | Lunch |
| 13:30 - 15:30 | Network lab We will start with an overview of traditional network analysis, covering theories of structural holes and weak ties, and relating them to graph theoretical notions of centrality and paths. We proceed with some more recent developments, covering diffusion and community structure. Finally, we discuss social balance theory, which relates to signed networks, making a connection to NLP. |
| 15:30 - 17:00 | Group assignment |
| 17:00 - 17:30 | Wrap up & drinks |
[Optionally: dinner]
Prerequisite knowledge
We intend the workhop to be suitable for graduate students from all disciplines. Because of this, we will not assume any particular skillset. Nonetheless, there will be some coding in python, because we aim to make the workshop practically relevant. It is therefore advisable to acquaint yourself with python if you have no experience yet. See also below for what software to install prior to the workshop.
Software
The workshop will be interactive, and we plan to switch between theoretical explanations and practical coding during class. Please bring your own laptop, with all prerequisite software installed. If you encounter any issue installing any software, please do not hesitate to contact one of the instructors.
We will use python 2 during our workshop. We will depend on the scipy stack, and it is recommended to use the Anaconda distribution especially if you are on Windows.
Some of the other packages we will rely on during the workshop are:
All can be installed in Anaconda (or using pip if you prefer).
It is practical to use python in for example ipython or spyder, both are included in the Anaconda distribution. In particular, the exercises and the labs will use jupyter notebooks, so please ensure that you have it installed.
All presentations, notebooks and assignments can be downloaded here.
Registration
Participation is free, but registration is required to help us plan the event accordingly: registration form. Registration closed the 5th of April.
Location
The seminar will be held at the INFORM space in the Designlab of the University of Twente.
Organizers
This is a 4TU Humans & Technology event. The lecturers:
- Vincent Traag (Leiden University)
- Dong Nguyen (Alan Turing Institute)
Backgroud reading (optional)
Courses
- Computational social science (Gatech 2015)
- Social Media Analysis and Computational Social Science (UMass 2015)
- Computational Social Science (Princeton 2016)
Tutorials
- Limits of Social Data (ICWSM 2016)
- Online Experiments for Computational Social Science (WWW 2015)
- Computational Social Science for the World Wide Web (WWW 2016)
Papers
General
- Lazer et al. (2009), Life in the network: the coming age of computational social science. Science, Vol. 323, Issue 5915, pp. 721-723.
Natural Language Processing
- Nguyen, D. & Doğruöz, A.S. & Rosé, A.S. & de Jong, F.M.G. (2016) Computational Sociolinguistics: A Survey. Computational Linguistics. Vol. 42, No. 3, Pages 537-593
- Bibliography on NLP and ethics: http://faculty.washington.edu/ebender/2017_575/
Social media
- Olteanu, A. & Castillo, C. & Diaz, F. & Kıcıman, E. (preprint) Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries
Textbooks
General
- Bishop, C. M. (2006). Pattern Recognition and Machine Learning. Springer. Cover, T. M., & Thomas, J. A. (2012). Elements of Information Theory (Vol. 2012). John Wiley & Sons.
- Hastie, T. & Tibshirani, R. & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer. Online available
- Murphy, K. P. (2012). Machine Learning: a Probabilistic Perspective. The MIT Press.
- Shalizi, C. R. (2013). Advanced data analysis from an elementary point of view
- Beazley, D., & Jones, B. K. (2013). Python Cookbook (2 edition). Sebastopol, CA: O’Reilly Media.
Networks
- Diestel, R. (2005). Graph Theory. Graduate Texts in Mathematics. Heidelberg: Springer.
- Newman, M. (2010). Networks: an introduction, Oxford University Press.
- Easley, D. & Kleinberg, J. (2010) Networks, Crowds, and Markets, Cambridge University Press. Online available
- Wasserman, S. & Faust, K. (1994) Social Network Analysis, Cambridge University Press (bit old but classic)
Natural Language Processing
- Jurafsky, D. & Martin, James H. Speech and Language Processing, Pearson. Draft of the 3rd edition is online available
- Manning, Chris & Schütze, Hinrich (1999) Foundations of Statistical Natural Language Processing, MIT Press.
- Bird, S. & Klein, E. & Loper, E., Natural Language Processing with Python – Analyzing Text with the Natural Language Toolkit. Online available