Citizen Participation and Machine Learning for a Better Democracy
dc.contributor.author | Procter, R | |
dc.contributor.author | Arana-Catania, M | |
dc.contributor.author | van Lier, F-A | |
dc.contributor.author | Tkachenko, N | |
dc.contributor.author | He, Y | |
dc.contributor.author | Zubiaga, A | |
dc.contributor.author | Liakata, M | |
dc.date.accessioned | 2021-08-27T10:43:57Z | |
dc.date.available | 2021-08-27T10:43:57Z | |
dc.date.issued | 2021-07-01 | |
dc.identifier.issn | 2639-0175 | |
dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/73792 | |
dc.description.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. | en_US |
dc.format.extent | 1 - 22 | |
dc.publisher | ACM | en_US |
dc.relation.ispartof | Digital Government Research and Practice | |
dc.rights | This item is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. | |
dc.rights | Attribution 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/us/ | * |
dc.title | Citizen Participation and Machine Learning for a Better Democracy | en_US |
dc.type | Article | en_US |
dc.rights.holder | © 2021, The Author(s) | |
dc.identifier.doi | 10.1145/3452118 | |
pubs.issue | 3 | en_US |
pubs.notes | Not known | en_US |
pubs.volume | 2 | en_US |
rioxxterms.funder | Default funder | en_US |
rioxxterms.identifier.project | Default project | en_US |
Files in this item
Files | Size | Format | View |
---|---|---|---|
There are no files associated with this item. |
This item appears in the following Collection(s)
Except where otherwise noted, this item's license is described as This item is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.