Course Introduction to Computational Social Science 2025

Materials, slides, hands-on code and assignments for for the course "Introduction to computational social science" for the 2025 edition

Here is the folder structure and what to expect:

• Root folder
  • This ReadMe.md text file
  • File named ".gitignore" is very important and described how it works in the slides of week on open-science and reproducibility
• Slides_PDF
  • slides for each week named as "W1_xx", "W2_xy" etc.
• Hands_on
  • There are instructions and example code for each week.

Note on using these materials

I am sharing the course materials publicly under a GPL-3.0 license. Please feel free to use these materials in your teaching or research. I ask you to give proper credit and link to this repository, if you used the materials, thanks.

Important announcements

Here I will copy announcements posted on Stud.IP so that everyone is informed about them.

2025-04-16 Preparation for our course's week 3 (tomorrow)

Dear Everyone,

Hope this email finds you very well.

For our session tomorrow at 11:15, I would like to ask you to do 2 things, please:

1. Please go over the slides for week 2 (shared last week in our course repository) and familiarize yourself with the content. Tomorrow, I will try to finish these slides, which will require going a bit faster, and it will help if you have checked the slides beforehand. Thanks.

2. Please go over chapters 1, 2 and 3 of Salganik's book (Bit by Bit; see slides of week 1 or list of literature in the course description in Stud.IP). If you have questions based on these two chapters, please bring them up so that we can discuss them tomorrow. Thanks.

See you tomorrow.

All the best, Ali

2025-04-17 Course's final assignment and examination

Dear Everyone,

Here is what we will do for the course's final assignment and examination.

In the two sessions preceding the last, which will take place on "Thu., 10/07/25, 11:15 - 12:45", I will share a list of topics with you. I will ask you to select one of these topics (among those I discussed in previous weeks of the course) as the topic of your practical assignment and do as I describe below.

In the course's final week on "Thu., 17/07/25, 11:15 - 12:45", all students should inform me about their selected topic/week.

For example, suppose a student selects the "Migration and Mobility" as the topic of their assignment. In that case, they will use the reading list for that week, search and find for other literature, plus use the data sources and research questions that I discussed, and prepare an example empirical analysis.

This empirical analysis should include the steps we discussed in the first week, i.e.,

1. In a report that you write that should be about 1,000 words or a maximum 5 A4 pages long (including figures, tables, and results that I discuss below), start with clarifying a research question, and provide an introduction on why it is important to answer this question.

2. What are the answers that literature has given to this question? Based on the literature, you should present a tentative answer to this question. You should properly cite the literature that you read and used to formulate your question (example: see APA style guide: https://apastyle.apa.org/style-grammar-guidelines/references/examples/journal-article-references).

3. A data source (examples that I introduce during the teaching can also be used) that could enable answering the question. For the example of migration and mobility, you may find a publicly accessible database that suits your short empirical analysis.

4. Your analytical strategy to take the data, analyze it, and answer the question. For instance, "The analysis plan is to run a regression model using variables M, N, O, X, from database WW to evaluate these variables' effect on the outcome variable, Y".

5. Your analysis code should be included in the folder I will assign to you in our shared repository. I prefer that you use R or Python for the analysis. The essay should also include the results that you found as tables or figures. Bonus point if you use plain text formats to write your essay which is under version control with Git! For instance, you can create a private repository for it and once finalized, copy/paste the final essay into our shared repository!

6. Did your results support the tentative answer based on the literature (see point 2 above) or refute it? Discuss what you learned from this empirical investigation.

7. What would you do next, and what would you suggest researchers reading your study's report do in the future? For example, is there a new research question that you can write about based on your study that someone else could take and answer in their future research?

The essay should be a maximum of 5 A4 pages. It should include these sections: a) introduction, b) background and literature, c) methods and analytical strategy, d) results, e) discussion and conclusion (including possible problems and limitations of your method and results), f) references (to both literature that you used, the data source that you collected or used etc.).

One hint on "where to find a good research question?" I recommend checking the "discussion" sections of the literature and articles I introduced in reading materials. They usually include what I wrote above, i.e., "future direction of research", you can select your question from those!

Please feel free to ask in our following sessions if the description above is unclear, thanks.

Best wishes,

Ali

2025-04-24 Installing Python using Pyenv for the hands-on part of week 3 and the following weeks

Dear everyone,

In the course yesterday, I shared some instructions on how to install R, RStudio, and Python (using Pyenv) on Mac, Linux, and Windows machines. I kindly ask you to follow the steps outlined in this file "https://github.com/akbaritabar/Course-introduction-to-computational-social-science-2025/tree/main/Hands_on/W3_DigitalTraceData" and if you had a problem while installing, please leave a comment in the issues section in this link: #2

In our next session, we will use the installed software. To save time, please follow the instructions on your own and install the software beforehand. Thank you.

Best,

Ali

2025-05-08 What to do at home before each week's session?

Dear everyone,

We had a great question today: "What should students do at home to prepare for the next course session?"

I answered, and here, I am providing more detail on how to use the course materials, slides, reading requirements, and additional recommendations.

The slides for each session are provided on the session's day (if not before). Please use the PDF and study it. Try to find things that were unclear to you. Send these points as questions to me by email and bring them to the next session so that we can discuss them. Each session's slides have a section on required and additional readings. Please go over these materials at your own pace, think about them, send your questions, and bring them for discussion.

The hands-on materials in each lab session are designed to be "a starting point", introducing you to the topic and providing a brief example. You could study these examples and send your questions.

Additionally, you are highly encouraged to extend these examples. For instance, if I provide one website as an example in a web scrapping exercise, you could practice finding another website and modifying the code to work for that new website. The same goes for APIs and other topics. If the examples show IMDB's API, try to find another one and modify the code to work with that new one.

Going over the reading materials, slides, hands-on codes, and examples will also prepare you for the final assignment of the course. You might already have a good idea of which session's topic interests you most. If you were lucky and this topic was included in the final exam's assignments list, you can pick it and do your assignment based on that topic!

Please let me know by email or open an issue in our shared GitHub repository (https://github.com/akbaritabar/Course-introduction-to-computational-social-science-2025) if something is unclear or a part of the code does not work. If instructions on installations lead to errors, please send them so that we can fix them. Please do not wait until the next session; send an email or open a GitHub issue so that we can figure out a solution. Thanks.

Best wishes, and see you next week!

Ali

2025-07-04 Topics for the final assignment of course on introduction to computational social science

Dear Everyone,

I hope you are doing well.

Here is the list of topics for the final assignment of the course on introduction to computational social science:

• Digital trace data and web scraping
• Migration and mobility
• Network analysis
• Text as data

For those of you who will take the final exam, please reply to this email by July 10 (or at the latest, July 17) and let me know your selected topic. Thanks.

It is completely fine if more than one person selects the same topic, but I expect your research questions and empirical cases to be distinct from each other. It is ideal to discuss with your colleagues the topic they are selecting and how to minimize overlap with your idea.

Further guidelines on the final assignment are available here on our repository: https://github.com/akbaritabar/Course-introduction-to-computational-social-science-2025/tree/main/ZZZ_Final_examination

If you have questions, I recommend using the time left until July 17th to ask them either by email or during our upcoming two sessions.

All the best, Ali

2025-07-04 How to hand over your essay and materials?

Create a "private" GitHub repository where you commit all these materials. Once you are finished, that should be by the handover deadline of 6 weeks after the course's final session, i.e., until August 28th, 2025, at midnight CEST (at the latest), add me as a collaborator to your "private GitHub repository".

This way, I can download (clone) your repository and access all the materials. Additionally, you show that you have learned how to create a repository and commit and push your materials to it.