Bovine Tuberculosis in Britain: identifying signatures of polarisation and controversy on Twitter

TL;DR

This study analyzes Twitter discussions on bovine tuberculosis and bovine viral diarrhoea in Britain, revealing differences in language, sentiment, and user profiles that reflect controversy and public opinion polarization.

Contribution

It introduces a comparative analysis of social media discourse on two livestock diseases, highlighting how language and user profiles differ in controversial versus non-controversial topics.

Findings

Distinct language and sentiment patterns for bTB and BVD tweets

User profile differences correlate with disease controversy

Network analysis reveals similar structural features across topics

Abstract

Approaches to disease control are influenced by and reflected in public opinion, and the two are intrinsically entwined. Bovine tuberculosis (bTB) in British cattle and badgers is one example where there is a high degree of polarisation in opinion. Bovine viral diarrhoea (BVD), on the other hand, does not have the same controversy. In this paper we examine how language subjectivity on Twitter differs when comparing the discourses surrounding bTB and BVD, using a combination of network analysis and language and sentiment analysis. That data used for this study was collected from the Twitter public API over a two-year period. We investigated the network structure, language content, and user profiles of tweets featuring both diseases. While analysing network structure showed little difference between the two disease topics, elements of the structure allowed us to better investigate the language structure and profile of users. We found distinct differences between the language and sentiment used in tweets about each disease, and in the profile of the users who were doing the tweeting. We hope that this will guide further investigation and potential avenues for surveillance or the control of misinformation.