Predicting and Analyzing Law-Making in Kenya
June 09, 2020 ยท Declared Dead ยท ๐ WINLP
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Oyinlola Babafemi, Adewale Akinfaderin
arXiv ID
2006.05493
Category
cs.CL: Computation & Language
Cross-listed
cs.CY,
cs.LG
Citations
0
Venue
WINLP
Last Checked
6 months ago
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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