research-article

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Citizen Participation and Machine Learning for a Better Democracy

Authors:

Miguel Arana-Catania,

Felix-Anselm Van Lier,

Nataliya Tkachenko,

Arkaitz Zubiaga,

Maria LiakataAuthors Info & Claims

Digital Government: Research and Practice, Volume 2, Issue 3

Article No.: 27, Pages 1 - 22

https://doi.org/10.1145/3452118

Published: 11 July 2021 Publication History

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Abstract

The development of democratic systems is a crucial task as confirmed by its selection as one of the Millennium Sustainable Development Goals by the United Nations. In this article, we report on the progress of a project that aims to address barriers, one of which is information overload, to achieving effective direct citizen participation in democratic decision-making processes. The main objectives are to explore if the application of Natural Language Processing (NLP) and machine learning can improve citizens’ experience of digital citizen participation platforms. Taking as a case study the “Decide Madrid” Consul platform, which enables citizens to post proposals for policies they would like to see adopted by the city council, we used NLP and machine learning to provide new ways to (a) suggest to citizens proposals they might wish to support; (b) group citizens by interests so that they can more easily interact with each other; (c) summarise comments posted in response to proposals; and (d) assist citizens in aggregating and developing proposals. Evaluation of the results confirms that NLP and machine learning have a role to play in addressing some of the barriers users of platforms such as Consul currently experience.

CCS concepts: • Human-centred computing→Collaborative and social computing • Computing methodologies→Artificial intelligence→Natural language processing

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cover image Digital Government: Research and Practice

Digital Government: Research and Practice Volume 2, Issue 3

Regular Papers

July 2021

102 pages

EISSN:2639-0175

DOI:10.1145/3474845

Editors:
Soon Ae Chun
City University of New York, USA
,
Beth Simone Noveck
The Governance Lab and New York University, USA

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Copyright © 2021 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Association for Computing Machinery

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Publication History

Published: 11 July 2021

Online AM: 04 May 2021

Accepted: 01 February 2021

Revised: 01 January 2021

Received: 01 June 2020

Published in DGOV Volume 2, Issue 3

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