Universität Wien
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200242 SE Theory and Empirical Research (Mind and Brain) 2 (2024S)

Introduction to computational social science

8.00 ECTS (4.00 SWS), SPL 20 - Psychologie
Continuous assessment of course work

Dieses Seminar kann für alle Schwerpunkte absolviert werden!
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 20 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 05.03. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 05.03. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 19.03. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 19.03. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 09.04. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 09.04. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 16.04. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 16.04. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 23.04. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 23.04. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 30.04. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 30.04. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 07.05. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 07.05. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 14.05. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 14.05. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 21.05. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 21.05. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 28.05. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 28.05. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 04.06. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 04.06. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 11.06. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 11.06. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 18.06. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 18.06. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 25.06. 15:00 - 16:30 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607
  • Tuesday 25.06. 16:45 - 18:15 PCR Computerhörsaal Psychologie, NIG 6.Stock A0607

Information

Aims, contents and method of the course

In the course Introduction to Computational Social Sciences, students learn how to use natural language processing tools to analyze the content of large numbers of texts automatically. Students learn to perform sentiment analyses of modern textual sources from the internet, such as movies and books, and online reviews of these media and others, such as video games, music, etc. Furthermore, students learn to analyze historical sources such as fiction works from the past. They can quantify the temporal change of values and preferences expressed in these sources and their relationship to historical events and socio-economic dynamics. Evaluation depends on three short assignments, a final project, and an oral presentation with Q&A. The course roughly covers the following modules:

Introduction to Python. Variables, numbers, strings, lists, loops, modules, and functions;
Introduction to modules. NLTK, Matplotlib, Regular Expressions, etc.;
Bag-of-words analyses. Preprocessing. Finding word synonyms and hyponyms using WordNet;
Word Embeddings. Building semantic clouds and navigating meaning spaces using Word2vec;
Pandas and simple visualizations: Creating datasets, word clouds, and frequency plots. Sentiment analysis. Overview and implementation of lexical and machine learning techniques;
Web scraping. Reading HTML/XML files with Beautiful Soup; Website interaction with Selenium;
APIs. Extracting structured information from social media and popular repositories;
Diachronic Analyses. Using psychometric tools to build valid bags-of-words; historical time series;
Designing studies and testing hypotheses. Relationship between historical events, socioeconomics, and word frequencies. Cross-correlations, lag analyses, and linear mixed models.

Assessment and permitted materials

50% Final Project Oral Presentation (Intro and Methods) and Q&A (Individual)
50% Class homework assignments, including 3 small assignments (3 x 10%) and a final project (20%) (Individual)

Minimum requirements and assessment criteria

>50% is necessary for a positive end result; >50% to 63% : grade 4, >63% to 75% : grade 3, >75% to 88% : grade 2, >88% : grade 1

Examination topics

All of which was covered in class

Reading list

Harvard python course:
- https://www.youtube.com/watch?v=nLRL_NcnK-4&t=7492s

Computational social science courses:
- https://ayoubbagheri.nl/applied_tm/
- https://github.com/JanaLasser/SICSS-aachen-graz
- http://digitalmedia.andreasjungherr.de/docs/intro.html
- Engel, U., Quan-Haase, A., Liu, S., & Lyberg, L. (Eds.). (2021). Handbook of Computational Social Science, Volume 2: Data Science, Statistical Modelling, and Machine Learning Methods (1st ed.). Routledge. https://doi.org/10.4324/9781003025245

Historical Psychology:
- Martins & Baumard (2022). How to develop reliable instruments to measure the cultural evolution of preferences and feelings in history? Frontiers in Psychology (13) https://osf.io/acukm/

Association in the course directory

Last modified: Tu 19.03.2024 12:26