Mapping Political-Elite Networks in Europe with a Multilingual Joint Entity-Relation Extraction Pipeline
arXiv:2606.27347v1 Announce Type: new Abstract: Whether political elites organise into rent-seeking coalitions that capture public resources or civic networks that sustain governance is a central question in comparative politics. Yet observing these complex, informal, and adversarial ties at scale has historically required intensive manual coding, while automated text-as-data methods have largely been limited to simple co-occurrence. Recent large language model (LLM) approaches offer a path forward but often rely on proprietary APIs, lack cross-lingual capability, and struggle with scalable en
The proliferation of advanced NLP techniques and interest in political analysis is enabling more sophisticated, automated methods for mapping complex social and political networks.
This research provides a more scalable and accurate method for understanding political influence and potential rent-seeking behavior, which is crucial for governance and public policy.
The ability to automatically map complex, informal elite networks at scale across languages offers a significant leap beyond previous manual coding or simple co-occurrence methods.
- · Political scientists and sociologists
- · Anti-corruption agencies
- · Computational linguists
- · Governments seeking transparent governance
- · Researchers relying on manual network analysis
- · Opaque political interest groups
More detailed and accessible mapping of political elite influence networks in Europe becomes possible.
This analytical capability could enhance transparency and accountability in governance, potentially exposing previously hidden ties.
The methodology could be adopted globally, leading to a new era of data-driven political oversight and potentially influencing international relations and accountability standards.
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Read at arXiv cs.CL