Sifting for Deeper Insights from Public Opinion: Towards Crowdsourcing and Big Data for Project Improvement

Tshimula, J.M., Njuguna, M.M., Bayala, T.R., Mbuyi, M.D., Essemlali, A., Kanda, H., Numfor, S., Sifting for Deeper Insights from Public Opinion: Towards Crowdsourcing and Big Data for Project Improvement, 2019 IEEE the 10th International Conference on Awareness Science and Technology, Morioka, Japan.

Abstract

Over the years, there seems to be a unidirectional top-down approach to decision-making in providing social services to the masses. This has often led to poor uninformed decisions being made with outcomes which do not necessarily match needs. Similarly from the grassroots level, it has been challenging to give opinions that reach the governing authorities (decision-making organs). The government consequently sets targets geared towards addressing societal concerns, but which do not often achieve desired results where such government endeavors are not in harmony with societal needs. With public opinions being heard and given consideration, societal needs can be better known and priorities set to address these concerns. This paper therefore presents a priority-based voting model for governments to collect public opinion data that bring suggestions to boost their endeavors in the right direction using crowdsourcing and big data analytics. View more…

Published by in AI and tagged Big Data and Public Opinion using 142 words.