Towards a new social media science

OVerview

The explosion of social media has created an unprecedented research opportunity for social scientists. Social media exposes a digital representation of society-in-motion: of people arguing, condemning, joking, influencing.

The growth of these digital spaces has coincided with the emergence of a family of tools - ‘big data analytics’ – that can make sense of them. Harnessing social media data as behavioural evidence using these tools could bring about a major evolution in the social sciences.

However, deriving meaning from these messy, contradictory data sets requires the development of new methodologies across the whole research field. The social sciences are concerned with collecting unbiased, representative samples; of analysing data in ways that reflect social reality; and of constructing more general explanatory theories, all according to an ethical frame that protects subjects of the research.

Current methods do little more than offer raw, descriptive accounts of social media phenomena drawn from convenient samples, with little additional enquiry or context.

The Project

This project, a collaboration with the University of Sussex and ESRC-funded, is designed to address these problems by creating an overall research system that can create insights – drawn from Twitter – that satisfy the standards of evidence demanded by social science.

To do this, it proposes to create new methodologies at each point of the research process:

1. Collection: Samples from Twitter are created by storing tweets that contain words that are searched for. Our sampling method will discover the search terms that statistically coincide with relevant tweets, and filter out tweets that are irrelevant. The system ‘cascades’: a constantly refreshing, statistically grounded, method of sampling that accommodates changes in how topics are discussed.

2. Analysis & Interpretation: Automated sentiment analysis classifies tweets at great volumes into meaningful categories. We will create categories that are informed by standing social science theory and the data itself, in order to draw inferences based on the data.

3. Ethics: Social media science entails a number of moral hazards that are not answered by conventional ethical frameworks. We will construct a new framework of social media science ethics on the basis of current public attitudes, possible harms to research subjects, and propose ways to measure and minimize them.

This will open up the value of social media to many different actors who have a stake in understanding people and society. Through publishing software and findings, and a series of training workshops aimed at both producers and consumers of research, the project investigators aim to spread the practice of rigorous, ethical social media science.

This project is supported by the National Centre for Research Methods and the ESRC.