Start:
End:
Monday, 24.8. 10:00
Tuesday, 25.8. 12:15
Language: English
Credit Points: 1 CP upon agreement with the lecturer
Course description:
This introductory course on Natural Language Processing (NLP) equips participants with both technical computational skills and critical perspectives on language and society. This course provides a hands-on introduction to NLP techniques, including data scraping, text preprocessing, word embeddings and Large Language Models (LLMS). Using a feminist lens, the course will explore how gender is portrayed differently on Wikipedia, uncovering biases in language and representation. By combining technical training with critical analysis, this course empowers participants to apply NLP tools to address gender inequalities and their facilitation in knowledge production.
Prerequisites:
This course welcomes participants from all backgrounds. Basic programming skills, preferably in R or Python, are recommended but not mandatory. Participants should ideally have an interest in Natural Language Processing and interdisciplinary fields that bridge computational and social sciences.
Biography: Mara Weber
Mara Weber is a PhD candidate in Social Research Methods in the Department of Methodology at the London School of Economics and Political Science (LSE). Previously, she was a predoctoral researcher in Computational Social Sciences (CSS) in the Department of Political Science at the University College London. She works on methodological innovations in the broader field of CSS and researches the malleability of collective memory and the durability of stigmatizing elite rhetoric. She holds a Bachelor of Arts in Sociology and a Master’s degree in Sociology and Social Research Methods from the University of Bremen.