Creating Social Science Datasets using Public APIs

Date:

04/06/2025

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 process of creating social science datasets using public APIs. Public APIs are a powerful tool for collecting data from a wide range of sources, including social media platforms, government agencies, and research organizations. In this course, we will cover topics such as data collection, data cleaning, and data curation using data collected from public APIs. We will also discuss best practices for working with public APIs, including how to handle rate limits, authentication, and pagination. We will use real-world examples to illustrate the concepts and methods covered in the course, and students will have the opportunity to create their own social science datasets using public APIs. By the end of the course, students will have a solid understanding of how to create social science datasets using public APIs, and will be able to apply these methods to their own research projects. A basic knowledge of programming (e.g., Python) is recommended for this course.

Session Details
Time: 10:00 - 15:00 (12:00 - 13:00 Lunch break)
Date: 4 June 2025
Mode: Hybrid - In person at CON 1.01 and on Zoom

All session materials and the Zoom link will be circulated after the sign-up closes on 2 June

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, Research Management and Impact, Research Skills, Communication and Dissemination


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
Research Management and Impact
Research Skills, Communication and Dissemination

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