“Politics on Speed - In Political Communication.”

This paper will explore accelerated politics in political communication. Rooted in the concept of acceleration (Rosa 2013), accelerated politics is defined as a constantly evolving system of implicit, often unexamined relations, rituals, and beliefs of how to compete for, gain, exercise and possess power in liberal democracies, influenced by technological and social acceleration. We see accelerated politics in increased mediatization and personalization of politics, stronger competition for power, algorithmic campaigning, higher voter volatility, increased political marketing, increased information complexity, and information overload as more bits of political information call for attention, because every political issue is subjected to urgency. The RQ will be: How do accelerated politics in different types of liberal democracies affect political communication, and with what consequences for democracy? The paper will 1) reflect how political acceleration have influenced political communication since the break-through of social media, and 2) study how political acceleration differentiate across different types of liberal democracies. The paper will empirically show that though political acceleration takes place, there is differences in how it is being distributed in political communication in different types of liberal democracies. The aim is to analyze the development from before the break-through of social media in 2006 and until today (2000-2024), in two Anglo-Saxon democracies (US and GB) and two Scandinavian democracies (Denmark and Sweden), to illustrate differences in the impact of accelerated politics in national political communication. There are differences in these countries regarding capitalism (Hall & Soskice 2001), political systems (Fukuyama 2014), and media systems (Reuters Digital News report, 2024), which is expected to shape how accelerated politics influence political communication. These differences can be traced in the speeches of political leaders, in rhetorical degrees of authoritarianism, conformism, cynicism, urgency, as well as appeal to distrust among voters. The data material will be publicly available political speeches of political leaders from 2000-2024, from all over the political spectrum in the last twenty years. The project will also explore the possibility of utilizing machine learning (ML) in the analysis, though the speech-data is expected to be too unstructured for ML-analysis.