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A Predictive Government Decision Based on Citizen Opinions: Tools & Results

Published: 04 April 2018 Publication History

Abstract

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.

References

[1]
Adel Rezk, M. et al. 2016. A Government Decision Analytics Framework Based on Citizen Opinion (Gov-DAF): Elaboration of the Knowledge Base Component. 6th International Conference on Information and Communication Technology (2016).
[2]
Adel Rezk, M. et al. 2015. A Proposed Government Decision Support System Based on Citizens Interactions over Social Networks. Proceedings of the FIFTH International Conference on Information and Communication Technology in Our Lives 2015 (2015).
[3]
Kelly, J.M. 2003. Citizen Satisfaction and Administrative Performance Measures Is there Really a Link? Urban Affairs Review. 38, 6 (2003), 855--866.
[4]
Kelly, J.M. and Swindell, D. 2002. A multiple--indicator approach to municipal service evaluation: correlating performance measurement and citizen satisfaction across jurisdictions. Public Administration Review. 62, 5 (2002), 610--621.
[5]
Percy, S.L. 1980. Response time and citizen evaluation of police. Journal of Police Science and Administration. 8, 1 (1980), 75--86.
[6]
Rezk, M.A. et al. 2016. A Government Decision Analytics Framework Based on Citizen Opinion. 9th International Conference on Theory and Practice of Electronic Governance (2016).
[7]
Ryzin, G.G. et al.h 2004. Drivers and consequences of citizen satisfaction: An application of the American customer satisfaction index model to New York City. Public Administration Review. 64, 3 (2004), 331--341.
[8]
Van Ryzin, G.G. 2004. Expectations, performance, and citizen satisfaction with urban services. Journal of Policy Analysis and Management. 23, 3 (2004), 433--448.
[9]
Skogan, W.G. 2005. Citizen satisfaction with police encounters. Police Quarterly. 8, 3 (2005), 298--321.
[10]
Stipak, B. 1979. Citizen satisfaction with urban services: Potential misuse as a performance indicator. Public Administration Review. (1979), 46--52.
[11]
Swindell, D. and Kelly, J.M. 2000. Linking citizen satisfaction data to performance measures: A preliminary evaluation. Public Performance & Management Review. (2000), 30--52.
[12]
de Walle, S. and Van Ryzin, G.G. 2011. The Order Of Questions In A Survey On Citizen Satisfaction With Public Services: Lessons From A Split-ballot Experiment. Public Administration. 89, 4 (2011), 1436--1450.
[13]
Welch, E.W. et al. 2005. Linking citizen satisfaction with e-government and trust in government. Journal of public administration research and theory. 15, 3 (2005), 371--391.T- Predictive

Cited By

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  • (2021)Over a decade of social opinion mining: a systematic reviewArtificial Intelligence Review10.1007/s10462-021-10030-2Online publication date: 25-Jun-2021

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  1. A Predictive Government Decision Based on Citizen Opinions: Tools & Results

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    cover image ACM Other conferences
    ICEGOV '18: Proceedings of the 11th International Conference on Theory and Practice of Electronic Governance
    April 2018
    739 pages
    ISBN:9781450354219
    DOI:10.1145/3209415
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 04 April 2018

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    Author Tags

    1. Citizen Satisfaction
    2. Decision Analytics
    3. Government Decision Support
    4. Opinion Mining
    5. Policy Acceptance Prediction
    6. Policy Aspects
    7. Semantic Relatedness
    8. Sentiment Analysis
    9. Social Media
    10. Topic Modeling
    11. Unstructured Text Analysis

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    ICEGOV '18

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    ICEGOV '18 Paper Acceptance Rate 104 of 184 submissions, 57%;
    Overall Acceptance Rate 350 of 865 submissions, 40%

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    • (2021)Over a decade of social opinion mining: a systematic reviewArtificial Intelligence Review10.1007/s10462-021-10030-2Online publication date: 25-Jun-2021

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