996010 Current methods in computational social science and computational sociology (StGr) (WiSe 2021/2022)

Computational social science and computational sociology are approaches that combine computer science and social sciences or sociology to make use of novel data types and sources to answer sociological and sociopolitical questions. This study group aims to discuss current methods used for the analysis of different data types relevant to these fields including text and video data, online data in general as well as geo-located data. For this, we draw on a pool of summer school classes that were provided to the public by excellent speakers of the field during July 2021 (https://socialdatascience.network/summerschool.html).

We plan to have 1 session every 2 weeks. The preparation time of each session will consist of watching the 4 hours long (recorded) class. We had a small survey among some people which topics are of interest and have thus selected 8 of the possible 16 classes (see below for an overview). If you are interested, you can also join in the off weeks to watch the class for the next week together.

We aim to discuss the contents of each class with respect to the following questions:

1. Open questions: Which parts were hard to understand, which parts did one struggle with? We will explain parts we did not understand to each other.

2. Possible applications: Where do we see the potential for an analysis involving such data (in our field)? We should probably make a living document we update along the course, as these research ideas will be very valuable information that should be preserved.

3. Examples: Small applications, analyses, or toy examples with some code if we have time or if someone tried to apply some methods after watching a video. Hopefully, the 2 weeks between each session gives us the time to sometimes have someone who already tried to use the method and eventually ran into some practical problems.

Below you can find the rough order of the classes. Preparation sessions are optional in a sense that you can either prepare the class at home or watch it with the others if you like.

[PREPARATION] Preparation of session 1

[SESSION 1 - 12.10.2021] Experimental Designs and Experimental Methodology https://socialdatascience.network/courses/experiementaldesigns.html

[PREPARATION - 19.10.2021] Preparation of session 2

[SESSION 2 - 26.10.2021] Social-media based experiments https://socialdatascience.network/courses/socialmedia.html

[PREPARATION - 02.11.2021] Preparation of session 3

[SESSION 3 - 09.11.2021] GeoData and Spatial Data Analysis with R https://socialdatascience.network/courses/geodata.html

[PREPARATION - 16.11.2021] Preparation of session 4

[SESSION 4 - 23.11.2021] Introduction to Machine Learning https://socialdatascience.network/courses/machinelearning.html

[PREPARATION - 30.11.2021] Preparation of session 5

[SESSION 5 - 07.12.2021] Natural Language Processing: Text classification https://socialdatascience.network/courses/NLP.html

[PREPARATION - 14.12.2021] Preparation of session 6

[SESSION 6 - 21.12.2021] Natural Language Processing: Topic Modeling https://socialdatascience.network/courses/nlptopic.html

[PREPARATION - 11.01.2022] Preparation of session 7

[SESSION 7 - 18.01.2022] Introduction to Deep Learning https://socialdatascience.network/courses/deeplearning.html

[PREPARATION - 25.01.2022] Preparation of session 8)

[SESSION 8 - 01.02.2022] Image as Data: quantitative image analysis with R and Python https://socialdatascience.network/courses/imageasdata.html