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; (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.
翻译:民主制度的发展是一项至关重要的任务,它被联合国选为联合国《千年发展目标》之一,从而证实了这一任务;在本条中,我们报告了旨在解决障碍的项目的进展情况,其中之一是信息负荷过大,目的是实现公民对民主决策进程的有效直接参与;主要目标是探讨应用自然语言处理和机器学习是否能改善公民对数字公民参与平台的经验;将“马德里决定”领事平台作为案例研究,使公民能够提出他们希望看到得到市议会通过的政策提案;我们利用国家语言和机器学习提供新的方法,以便:(a) 向公民建议他们可能希望支持的建议;(b) 按利益将公民组织起来,以便他们能够更容易地相互交流;(c) 总结在回应建议时发表的评论;(d) 协助公民汇总和拟订建议;对结果的评估证实国家语言和机器学习在解决诸如领事目前的经验等平台的一些使用障碍方面可发挥作用。