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Towards Effective E-Participation of Citizens in the European Union: The Development of AskThePublic

Nils Messerschmidt, Kilian Sprenkamp, Amir Sartipi, Xiaohui Wu, Igor Tchappi, Liudmila Zavolokina, Gilbert Fridgen

TL;DR

The paper tackles the challenge of extracting actionable, trustworthy insights from EU e-participation feedback by introducing AskThePublic, an LLM-enabled chatbot guided by Media Richness Theory. Built via Design Science Research, the system uses a retrieval-augmented generation pipeline to transform Have Your Say input into real-time, multilingual, and structured feedback for policymakers, journalists, researchers, and citizens. Evaluation through 11 interviews demonstrates increased perceived interactivity and clarity, while highlighting concerns about source credibility, potential biases, and data limitations. The work offers practical design recommendations and identifies key user groups, signaling a path toward more participatory and transparent EU governance, with opportunities to adopt open-source LLMs and broaden validation in future iterations.

Abstract

E-participation platforms are an important asset for governments in increasing trust and fostering democratic societies. By engaging public and private institutions and individuals, policymakers can make informed and inclusive decisions. However, current approaches of primarily static nature struggle to integrate citizen feedback effectively. Drawing on the Media Richness Theory and applying the Design Science Research method, we explore how a chatbot can address these shortcomings to improve the decision-making abilities for primary stakeholders of e-participation platforms. Leveraging the "Have Your Say" platform, which solicits feedback on initiatives and regulations by the European Commission, a Large Language Model-based chatbot, called AskThePublic is created, providing policymakers, journalists, researchers, and interested citizens with a convenient channel to explore and engage with citizen input. Evaluating AskThePublic in 11 semi-structured interviews with public sector-affiliated experts, we find that the interviewees value the interactive and structured responses as well as enhanced language capabilities.

Towards Effective E-Participation of Citizens in the European Union: The Development of AskThePublic

TL;DR

The paper tackles the challenge of extracting actionable, trustworthy insights from EU e-participation feedback by introducing AskThePublic, an LLM-enabled chatbot guided by Media Richness Theory. Built via Design Science Research, the system uses a retrieval-augmented generation pipeline to transform Have Your Say input into real-time, multilingual, and structured feedback for policymakers, journalists, researchers, and citizens. Evaluation through 11 interviews demonstrates increased perceived interactivity and clarity, while highlighting concerns about source credibility, potential biases, and data limitations. The work offers practical design recommendations and identifies key user groups, signaling a path toward more participatory and transparent EU governance, with opportunities to adopt open-source LLMs and broaden validation in future iterations.

Abstract

E-participation platforms are an important asset for governments in increasing trust and fostering democratic societies. By engaging public and private institutions and individuals, policymakers can make informed and inclusive decisions. However, current approaches of primarily static nature struggle to integrate citizen feedback effectively. Drawing on the Media Richness Theory and applying the Design Science Research method, we explore how a chatbot can address these shortcomings to improve the decision-making abilities for primary stakeholders of e-participation platforms. Leveraging the "Have Your Say" platform, which solicits feedback on initiatives and regulations by the European Commission, a Large Language Model-based chatbot, called AskThePublic is created, providing policymakers, journalists, researchers, and interested citizens with a convenient channel to explore and engage with citizen input. Evaluating AskThePublic in 11 semi-structured interviews with public sector-affiliated experts, we find that the interviewees value the interactive and structured responses as well as enhanced language capabilities.

Paper Structure

This paper contains 14 sections, 2 figures, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. Citizen Involvement in the EU
  4. Media Richness Theory
  5. Large Language Models
  6. Methodology
  7. Results
  8. Problem Statement & Solution Objectives
  9. Artifact Design
  10. Demonstration and Evaluation
  11. Discussion
  12. Designed Artifact and Future Research
  13. Possible User Groups
  14. Conclusion

Figures (2)

  • Figure 1: Analysis page displaying a detailed response to the user's query
  • Figure 2: The RAG pipeline