East African Scholars Journal of Engineering and Computer Sciences Abbreviated Key Title: East African Scholars J Eng Comput Sci ISSN: 2617-4480 (Print) & ISSN: 2663-0346 (Online) Published By East African Scholars Publisher, Kenya Volume-5 | Issue-5 | Sept-2022 | DOI: 10.36349/easjecs.2022.v05i05.002 *Corresponding Author: Malachi Omela Manases 69 Master Student, Department of Information Technology, Kabarak University, Kenya Original Research Article Sentiment Analysis Model for Public Participation Forums in County Governments Malachi Omela Manases 1* , Moses Thiga 2 , Nelson Masese 2 1 Master Student, Department of Information Technology, Kabarak University, Kenya 2 Senior Lecturer, Department of Information Technology, Kabarak University, Kenya Article History Received: 19.08.2022 Accepted: 24.09.2022 Published: 29.09.2022 Journal homepage: https://www.easpublisher.com Quick Response Code Abstract: Public participation is important because it helps to close the gap between the public, private sector and the government. However, a successful devolution process in Kenya is hampered by a lack of/inadequate public participation in county governments. Communications gaps are one of the arguments made for this development. The main objective of the study was to develop a sentiment analysis model for use in public participation forums in County Governments in Kenya. The study was conducted through the design thinking process. The population of interest of this study comprised of county management and staff also area residents in Nakuru, Busia and Baringo counties who have participated in public participation forums before. The Bidirectional Encoder Representations from Transformers (BERT) approach was used to create the cloud NLP package and obtain user sentiment magnitudes for the sentiment analysis model. Following that, cross validation was utilized to assess the performance indicators during the design stage, and users took part in the model's assessment. The overall conclusion of validation is that the model performed as expected and recorded instrumental results in increasing effective public participation in county governments in Kenya and strengthen the devolution process. This study recommends that the model can be cascaded to all the counties in Kenya to improve the efficiency of public participation. Keywords: Public participation, (BERT), Sentiment Analysis Model. Copyright © 2022 The Author(s): This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY-NC 4.0) which permits unrestricted use, distribution, and reproduction in any medium for non-commercial use provided the original author and source are credited. INTRODUCTION Technology is viewed as a solution to social issues. Public participation is not an exception. Every county government in Kenya has an official website which is often used to access information. The requisite documents for public participation are posted on the website (Transparency International Kenya, 2018). Effective participation needs transparency (Daudi, 2016). Transparency in public’ actions and transparency in leadership and administration. Openness is affected through access to information. Inadequate access leads to difficulty in interpreting the policies, services and programs. Public apathy is the indifference, lack of concern in development. When there is apathy among the public means that there are disinterested leading to them withdrawing from participation (Obora, 2016). Sentiment Analysis Sentiment analysis (SA) which is also referred to as emotion AI or opinion mining can be defined as the process of automating mining of opinions, views, attitudes, emotions and phrases through Natural Language Processing (Beigi, Hu, Maciejewski & Liu, 2016). It is the application of text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to the voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine. Sentiment Analysis is extremely useful in social media monitoring as it allows us to gain an overview of the wider public opinion behind certain topics. The applications of sentiment analysis are broad and powerful. The ability to extract insights from social data is a practice that is being widely adopted by organizations across the world.