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 combining theoretical explanations with actual coding. In the group assignments, we will stimulate an integrated approach to both NLP and network analysis.
Participation is free, but registration is required to help us plan the event accordingly. Please go the website of the lecturers (https://vtraag.github.io/4TU-CSS/) to register for this seminar. The website also provides information about prerequisite knowledge and software that will be used during the seminar.
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