Big data driven e-government framework in Nigeria

Autor: Kolajo Taiwo, Virginia E. Ejiofor, Emeka Ogbuju, Moses Okechukwu Onyesolu
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: Bayero Journal of Pure and Applied Sciences; Vol 11, No 2 (2018); 252-259
ISSN: 2006-6996
Popis: Many nations of the world are employing the use of big data in e-government for integrated policy making. However, in Nigeria, data-driven decision making is still a challenge due to lack of a centralized framework that can integrate different silo data centers for insightful and evidence- based governance. The paper proposes a big data-driven e-government framework for e- governance operations. The framework was designed in the Nigerian context using big data mechanisms. It was tested with an experiment that performed a sentiment analysis to uncover the opinion of the masses on selected agencies in order to help policy making. This was done with datasets collected from the social media handles of two (2) government agencies – the Nigerian police force and the Nigerian army. The results uncovered the actual opinions of the populace concerning both agencies as it regards national security. The framework promises a host of benefits such as centralized data entry point for governance, data harvesting system, seamless integration and collaboration of government operations and an easy application of open data policy. The paper concludes with four (4) recommendations which the government of any developing nation can imbibe for results-oriented e-governance and increase the quality of service to citizens and businesses. Keywords: big data, data, e-government, e-governance, framework, hadoop, sentiment analysis
Databáze: OpenAIRE