Online Exposure to Political and Ideological Content

Evidence from Surveys, Web Browsing Histories and Social Media Data

Iulia Cioroianu, University of Bath

In order to understand change (and stability) in political opinions and behaviour, it is necessary to measure the information individuals are exposed to. The internet and social media allow users to interact, collaborate, create and share information in virtual spaces and communities, and have radically changed the political information environment, including the types of content the public is exposed to as well as the exposure process itself. Individuals are faced with a wider range of options (from social and traditional media), new patterns of exposure (socially mediated and selective) and alternate modes of content production (e.g. user-generated content). This talk provides an overview of the main data collection, processing and text analysis methods which can be used to measure and analyse the political information consumed and shared in this dynamic and interconnected online environment.

The methods presented were used by the ExpoNet project team to study online information exposure over the course of the Brexit Referendum campaign. By linking three types of data (surveys, individual web browsing histories and social media data), we were able to: a. evaluate the popularity of different topics and issues during the campaign; b. examine whether online news exposure exhibits signs of segregation and selectivity by capturing exposure to both traditional news sources and news shared via social media platforms; c. examine what types of individuals are more likely to exhibit selective tendencies; d. compare the topics and ideological leanings of articles read during in referendum campaign with those of articles shared on Twitter.

The presentation provides an overview of the ways in which various methods (web scraping,
social media data collection, storage and processing, keyword and dictionary methods, cosine similarity, supervised classification and topic modelling) were combined in a large-scale research project. Moving closer to a causal identification strategy, I also present ongoing work on a web application which informs users about the ideological leaning of the articles they read and allows researchers to account for self-selection effects in information exposure.

How can we measure meaning?

Citizen portrayals in the news media

Zoltan Fazekas, Copenhagen Business School

The media play a crucial role in the dissemination of politically relevant information, through
simple news articles, opinion pieces or political talk shows among others. The content presented on various news platforms serves as input for many citizens, potentially influencing how people learn about politics or how they perceive political realities. Accordingly, we strive to understand what the news media talks about, why, and how they present information. With technological advances and growing digital archives, quantitative text analysis tools have been used extensively to advance the study of political communication.

In this talk I will first review two quantitative text analysis approaches often used to study
political media content: sentiment analysis and topic models. The main aim is to categorize the type of insights these approaches can offer and focus on the validation requirements. After mapping what these approaches cannot tell us, I introduce word embeddings as a tool to capture a distributional theory of language. This can facilitate our attempts to retrieve the meaning of various words of interest by relying on their context and use. The talk concentrates on an applied example where I contrast the features of the methods reviewed.

Analyzing the Brexit-related news coverage from 2016, the study deals with the potential
measurement of exclusionary (media) populism through systematic differences in the portrayal of citizens. While previous research has treated the outgroup as homogenous and analyzed the broad category of migrants, we focus on a case with multiple (potential) outgroups. Both migrants and EU citizens were established as outgroups: both were portrayed in a very similar manner in the news, but very dissimilar to U.K. citizens. These stark distinctions appear despite the lack of strong sentiment differences in the citizen portrayals and the presence of common broader political topics discussed when these mentions are made. Finally, the results bring further evidence for a convergence between tabloids and broadsheets, as differences in the degree of exclusionary media populism are negligible.