This project seeks to quantify trends and changes in the volatility of public opinion before and after widespread use of social media, and to study how social information can drive public opinion.

Overview

Recent election surprises, regime changes and political shocks seem to indicate that the public agenda has become more fast-moving and volatile. One of the likely components of this political turbulence is the recent change in how we acquire and consume information. Yet, there has been no systematic investigation into the nature of this volatility, of the individual bases of political opinion formation, or its potential impact on the policy-making landscape. This project seeks to address this gap in knowledge by quantifying the level of volatility in the ‘issue attention’ economy, and studying the relation between social information and political opinion.

Social media platforms have been shown to inject instability and uncertainty into social life, public opinion, civil society, and the policy-making environment. They exert social influence on users by showing in real time what other people are doing (social information), as well as reducing the costs of becoming visible, and so increasing the likelihood of acting. Individual acts of participation in turn create further social information, which may influence someone else’s decision about whether to act, leading to feedback cycles and chain reactions.

These feedback influences at work on social media platforms have been shown to introduce instability into cultural markets, and have now penetrated the ‘issue attention’ economy and the policy-making landscape, creating political turbulence. This disorganised environment, in which fluid and overlapping groups of individuals mobilise around common (often temporary) social issues and goals, manifests itself, for example, in a highly unequal distribution of participants; most YouTube or Facebook videos have very few views while a small number are watched millions of times, accumulating these views quickly and dramatically.

We are using natural language processing and information theoretic approaches to quantify the trends and changes in the volatility of public opinion before and after social media became widely used, by looking at with seventy years’ worth of public opinion polling and media coverage data from the UK and Germany. To understand the effects of exposure to social information on individual political opinion, we are drawing on methods from experimental psychology and social data science.

Understanding the ways in which social information affects the dynamics of political opinion will shed light on the role of social media platforms, leading to a more thorough understanding of the undercurrents of public opinion that have, in recent years, burst to the surface in highly unpredictable ways. This can inform the creation of early warning signals that may aid in prediction and explanation of public opinion dynamics, improve the opportunities to help policy makers understand and represent the will of their constituents, and guide the design of better online platforms for social interaction.

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