Predicting and Analyzing Law-Making in Kenya

• URL: http://arxiv.org/abs/2006.05493v1
• Date: Tue, 9 Jun 2020 20:21:50 GMT
• Title: Predicting and Analyzing Law-Making in Kenya
• Authors: Oyinlola Babafemi and Adewale Akinfaderin
• Abstract summary: We developed and trained machine learning models on a combination of features extracted from the bills to predict the outcome. We observed that the texts in a bill are not as relevant as the year and month the bill was introduced and the category the bill belongs to.
• Score: 0.012691047660244334
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Modelling and analyzing parliamentary legislation, roll-call votes and order of proceedings in developed countries has received significant attention in recent years. In this paper, we focused on understanding the bills introduced in a developing democracy, the Kenyan bicameral parliament. We developed and trained machine learning models on a combination of features extracted from the bills to predict the outcome - if a bill will be enacted or not. We observed that the texts in a bill are not as relevant as the year and month the bill was introduced and the category the bill belongs to.

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