MURAL - Maynooth University Research Archive Library

    A predictive government decision based on citizen opinions - tools & results

    Rezk, Mohamed Adel and Ojo, Adegboyega and El Khayat, Ghada A. and Hussein, Safaa (2018) A predictive government decision based on citizen opinions - tools & results. In: ICEGOV '18: Proceedings of the 11th International Conference on Theory and Practice of Electronic Governance. Association for Computing Machinery (ACM), pp. 712-714. ISBN 9781450354219

    Download (849kB) | Preview

    Share your research

    Twitter Facebook LinkedIn GooglePlus Email more...

    Add this article to your Mendeley library


    Research on citizen satisfaction with respect to public policies has significant public and political value. Politicians are generally seeking effective public policies that favourably impacts citizens’ satisfaction. Citizen satisfaction index is a plausible mechanism for public policy makers to monitor and evaluate the public policies. While surveys on citizen satisfaction are common among agile and progressive public administration and governments, automating the computation of citizen's’ satisfaction is challenging. Given that surveys and evaluations related to citizen satisfaction are retrospective, remedial actions when necessary are always somewhat late. We describe in this poster a predictive analytics framework for citizen satisfaction with respect to public policy based on the previous citizen sentiments past related policies.

    Item Type: Book Section
    Keywords: Government Decision Support; Decision Analytics; Policy Acceptance Prediction; Citizen Satisfaction; Policy Aspects; Opinion Mining; Sentiment Analysis; Semantic Relatedness; Topic Modeling; Social Media; Unstructured Text Analysis;
    Academic Unit: Faculty of Social Sciences > School of Business
    Item ID: 13369
    Identification Number:
    Depositing User: Adegboyega Ojo
    Date Deposited: 02 Oct 2020 15:00
    Publisher: Association for Computing Machinery (ACM)
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

    Repository Staff Only(login required)

    View Item Item control page


    Downloads per month over past year

    Origin of downloads