Research Papers
Below are the team’s recent publications and ongoing research papers. Archived publications can be found on the researchers’ personal pages.
Muskian Futurism
Jamie Ranger, Will Ranger
Muskian futurism describes a cluster of political ideas and beliefs centred on Elon Musk. This paper defines it as an overlapping constellation of contemporary futurism, cyber-libertarianism, neo-reaction, white supremacism, and personal self-interest, united by a shared diagnosis of the world and aligned with actors around the second Trump administration. Unlike nationalism, it is driven by technological solutionism and indifference to Musk’s pursuit of self-interest. The paper argues that Muskian futurism functions as a form of technocratic accelerationism that threatens democratic institutions.
Populism in the Technospheric
Jamie Ranger
The paper argues that today’s technospheric environment — shaped by social acceleration, the industrialization of memory, and mediatization — serves as a structural catalyst for the repoliticisation of the status quo. In this context, Ernesto Laclau’s discursive approach to populism needs to be reconsidered. The paper shows that contemporary social life exacerbates social problems and provoke counterhegemonic responses. These responses are not only shaped by populist strategy but also increasingly influenced by algorithmic steering on social media. Thus, the technospheric condition both fuels and complicates the dynamics of populism, as it simultaneously amplifies social disruptions and mediates their expression.
Populism in Power: How Ideological Commitments Shape Digital Governance Strategies
Juan S. Gómez Cruces, Ewan Thomas-Colquhoun and Estariol de la Paz
Populist governments have competing interests where it comes to digital policy. They frequently use digital platforms to construct and communicate with ‘the people’ for whom they claim to speak, yet often curb online freedoms on those same platforms once in power.
Our comparative study interrogates this tension, using the political alignment of populist leaders along left-right and liberal-illiberal cleavages. Ten populist episodes across diverse political contexts are analysed, using the augmented synthetic control method to construct counterfactual trajectories for each country as a means to identify the impact of populism on digital governance.
We find that ideological positioning provides a statistically significant explanation for digital governance divergence, with support for liberal democratic values a stronger predictor for changes in internet freedoms than the left-right divide. For academic approaches to populism, greater attention to its ideological variations is required to understand how populism in power shapes political processes.
Automated Political Stance Identification in Political Texts: A Theory-Driven and Transparent Approach
Juan S. Gómez Cruces, Yorick Scheffler, and Ewan Thomas-Colquhoun
This paper introduces a transparent, theory-driven method for automatically identifying political stances in text using Burnham et al.'s (2024) Political DEBATE model, a light-weight Natural Language Inference (NLI) classifier specialized for political discourse.
Building on established political science theories, we adapt conceptual definitions from expert surveys into natural-language hypotheses which are evaluated against premise texts in a zero-shot setting to identify ideological entailment. Using this approach, we classify texts along three key dimensions of political competition: economic left–right ideology, populist versus pluralist rhetoric, and support for liberal democratic values. We validate the method by applying the model to a diverse sample of political texts and comparing its outputs with expert-coded assessments.
For the left–right and populism–pluralism dimensions, the model produces scores statistically indistinguishable from expert evaluations, demonstrating accuracy within the expert range. Unlike supervised or fine-tuned approaches, our method requires no additional labeled training data, reduces computational and financial costs, and provides high transparency, as every stance score can be traced back to explicit hypotheses grounded in political science theories.
Finally, we integrate this methodology into the Automated Political Stance Identification (APSI) platform, offering researchers, practitioners, civil society organizations, policymakers, and the broader public an accessible tool for systematically evaluating positions in political discourse.
Venerable Representation: AI-Generated Synthetic Media in the 2024 Elections in India and Pakistan
Jamie Ranger, Umer Jan, Estariol de la Paz, Sonakshi Saha
This paper examines the recent emergence of venerable representation, the use of AI-generated synthetic media by politicians and their parties to present a favourable image of themselves, rather than discredit adversaries.
We argue that in contexts such as South Asia where AI deployment is considered neutral or positive, politicians can generate synthetic content for purposes of mystification, revivification and ventriloquism. After critical analysis of three cases — Arwind Kejriwal, Buddhadeb Bhattacharjee, and Imran Khan — we conclude that if usage of AI synthetic media becomes increasingly normalised and rapidly improved, further examples in future elections around the world will warrant greater scrutiny for fear of undermining the relationship between politicians and their publics.