Applied Language Models for Social Science Research - Dr Zach Dickson

Date:

12/02/2025

Organised by:

London School of Economics

Presenter:

Dr Zach Dickson

Level:

Advanced (specialised prior knowledge)

Contact:

Crystal Chia
methodology.research@lse.ac.uk

Map:

View in Google Maps  (WC2B 4DS)

Venue:

CON 1.01,
Connaught House,
LSE
65 Aldwych
London

Description:

This course will introduce students to the use of language models for social science research. Language models are a type of machine learning model that can be used to analyse text data. They have been used in a wide range of applications, from sentiment analysis to machine translation, and have especially gained spotlight following the launch of OpenAI’s ChatGPT. In this course, we will focus on how language models can be applied to social science research. We will cover topics such as text classification, topic modeling, and text generation. We will also learn how to use language models to create training data, and we will discuss methods for evaluating the accuracy of language models and reporting metrics in academic research. Finally, we will consider the limitations and ethical implications of using language models in social science research. By the end of the course, students will have a solid understanding of how to apply language models to their own research projects. A basic knowledge of programming in Python is recommended for this course.

Session Details
Time: 10:00 - 15:00 (12:00 - 13:00 Lunch break)
Date: 12 February 2025
Mode: Hybrid - In person at CON 1.01 and on Zoom

Cost:

Free

Website and registration:

Register for this course

Region:

Greater London

Keywords:

Frameworks for Research and Research Designs, Data Collection, Data Quality and Data Management , Quantitative Data Handling and Data Analysis, Mixed Methods Data Handling and Data Analysis, ICT and Software, Quantitative Software


Related publications and presentations from our eprints archive:

Frameworks for Research and Research Designs
Data Collection
Data Quality and Data Management
Quantitative Data Handling and Data Analysis
Mixed Methods Data Handling and Data Analysis
ICT and Software
Quantitative Software

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