This free webinar, organised by the UK Data Service, is the second in a series of three on understanding and using SNA methods for social science research purposes. In this webinar we demonstrate how to collect and clean social network data. In particular, we draw on two sources of social network data:

Vast swathes of our social interactions and personal behaviours are now conducted online and/or captured digitally. Thus, computational methods for collecting, cleaning and analysing data are an increasingly important component of a social scientist’s toolkit. Social Network Analysis (SNA) offers a rich and insightful methodological approach for uncovering and understanding social structures, relations and networks of association.

This free webinar, organised by the UK Data Service, is the second in a series of three on understanding and using SNA methods for social science research purposes. In this webinar we demonstrate how to collect and clean social network data. In particular, we draw on two sources of social network data:

The social media platform Twitter, which allows restricted access to some of its data through an Application Programming Interface (API)

Administrative data on UK charities, which is publicly available and can be repurposed for social network analysis

As a result of attending this webinar, participants will understand the steps necessary for collecting, cleaning and reshaping data for social network analysis.

Details:

Level: Introductory, for individuals with no prior knowledge or experience of social network analysis

Duration: 45 minutes, followed by questions

Pre-requisites: The following webinars cover useful background knowledge and skills:

- Social Network Analysis: Basic Concepts

- APIs as a Source of Data

Audience: Researchers and analysts from any disciplinary background interested in employing network analysis for social science research purposes

Programming language: Python

Materials: Participants will have access to an interactive online notebook through which they can practice collecting and cleaning social network data using Python

Learning outcomes: Understand the main steps in collecting, cleaning and reshaping data for social network analysis and be able to use Python for working with social network data