Affiliation:
1. University College Dublin, Ireland
Abstract
Can social media revert the top-down dynamics of securitization? Limited by the notion that ‘security is only articulated in an institutional voice by the elites’, the role of non-elite actors has remained understudied. Only recently has it been proposed that lay actors can become influential security agents through their online activity. However, social media’s capacity to revert the top-down dynamics of securitization remains contended. To explore this puzzle and seeking to update the theory of securitization to the modern context of political communication, this study employs a semi-supervised machine learning approach to analyse a novel dataset of over 10 million Twitter messages by five elite and non-elite actor groups discussing the Amazon rainforest fires in 2019. Finally, the study uses vector autoregression (VAR) models to explore who leads and who echoes the securitization process. The results show that both elite and lay actors behave as security agents and demonstrate the methodological contribution offered by the text-as-data approach developed in this analysis.
Funder
University College Dublin
Subject
Sociology and Political Science,Communication