In person icon Foreign Information Manipulation and Interference: Actors, Practices, Concepts

Abstract

This panel brings together three complementary papers that explore different aspects of Foreign Information Manipulation and Interference (FIMI) tactics, particularly those used by autocracies, focusing on actors, practices, and concepts and applying strategic historical analysis and modern detection methods. The first paper presents a historical analysis of Russian and Chinese strategies for FIMI, offering a deep dive into the evolution of their military and information warfare doctrines. By reviewing official documents, reports, and scholarly literature, the paper identifies trends and patterns in their foreign interference efforts. It sheds light on how these nations' approaches to information warfare and cyber operations have evolved, ultimately contributing to a broader understanding of their objectives and methodologies. The second paper tackles the current challenges in countering Russian and Chinese FIMI, particularly within the context of the European Union. Based on findings from 21 semi-structured interviews with policy experts and stakeholders, the research examines the conceptual and operational issues faced when dealing with FIMI in EU. It critically explores gaps in the EU's FIMI framework, as proposed by the European External Action Service (EEAS), and suggests areas for improvement in responding to the rapidly evolving nature of FIMI tactics. Additionally, the paper discusses the trade-offs between external defense measures and the potential for domestic censorship. The study's findings contribute to FIMI scholarship and offer actionable insights for enhancing the EU's defensive strategies against foreign influence operations carried out by Russia and China. The third paper focuses on the application of advanced computational methods to detect FIMI in large global datasets. By leveraging large language models (LLMs) and entity extraction algorithms, the research introduces a novel pipeline for detecting FIMI-related entities, events, and narratives. This innovative approach integrates political science frameworks with computational linguistics, aiming to automate the detection of disinformation and influence operations. The study analyzes data from platforms such as ACLED and Google Trends, utilizing Named Entity Recognition (NER) and topic modeling to identify anomalies that could signal coordinated FIMI campaigns. The approach is validated through human coding, ensuring accuracy and reliability. This paper contributes to the growing field of automated FIMI detection, addressing critical gaps in the capacity to identify and classify disinformation at scale. Together, these papers offer a multifaceted exploration of FIMI and its role in building alternative global governance of information ecosystems. They provide a comprehensive understanding of foreign interference strategies and contribute to the development of more effective responses to information warfare.

Title	Details
War as a Catalyst: Russia’s Public Diplomacy on Chinese Social Media During the Russo-Ukrainian War	View Paper Details
Beyond Western Media Hegemony: Türkiye's International Media as Illiberal Norm Entrepreneurs	View Paper Details
Capturing FIMI in Strategic and Military Doctrines of Russia and China	View Paper Details
In Their Own Words: Capturing Stakeholders’ Views on How to Strengthen the EEAS FIMI Framework	View Paper Details
From Algorithms to Actors: Detecting Foreign Interference Through Entity Extraction and LLM-Based Methods	View Paper Details