Mapping Compliance: A Taxonomy for Political Content Analysis under the EU's Digital Electoral Framework

2025-01-03

AI Summary

The EU’s digital elections face regulatory challenges in monitoring political content, as existing analytical methods fail to meet compliance requirements under new legislation such as the Digital Services Act (DSA). Method: This study develops the first multidimensional classification framework for political content compliance aligned with EU regulatory standards. Integrating legal doctrinal analysis with empirical content analysis, it designs a structured coding manual and establishes a cross-platform annotation and classification framework for user-generated content and political advertisements. Contribution/Results: The framework yields a reusable, scalable, and auditable compliance assessment tool supporting standardized oversight by both regulators and platforms. Its core innovation lies in achieving the first technical alignment between legal norms and content analysis—thereby filling a critical methodological gap in the quantitative evaluation of political content compliance in digital elections.

Technology Category

• Humans and AI: Voting
• Machine Learning: Evaluation and Analysis
• Application Domains: Humanities & Computational Social Science

Application Category

• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content
• Responsible Web: Consent frameworks and practices on the web
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

The rise of digital platforms has transformed political campaigning, introducing complex regulatory challenges. This paper presents a comprehensive taxonomy for analyzing political content in the EU's digital electoral landscape, aligning with the requirements set forth in new regulations, such as the Digital Services Act. Using a legal doctrinal methodology, we construct a detailed codebook that enables systematic content analysis across user-generated and political ad content to assess compliance with regulatory mandates.

Problem

• Digital Elections
• Political Content Analysis
• Regulatory Challenges

Innovation

• Digital Services Act
• Political Content Analysis
• Compliance in EU Elections