A government decision analytics framework based on citizen opinion

Mohamed Adel Rezk; Ghada A. El Khayat; Adegboyega Ojo; Safaa Hussein

doi:10.1145/2910019.2910093

A government decision analytics framework based on citizen opinion

Mohamed Adel Rezk, Ghada A. El Khayat, Adegboyega Ojo, Safaa Hussein

Research output: Chapter in Book or Conference Publication/Proceeding › Conference Publication › peer-review

Abstract

This ongoing research aims to develop a Government Decision Support Framework that employs citizen opinions and sentiments to predict the level of acceptance of newly proposed policies. The system relies on a knowledge base of citizen opinions and an Ontological Model comprising aspects and related terms of different policy domains as an input and a Bayesian predictive procedure. The work proceeds in four basic steps. The first step involves developing domain models comprising aspects for different policy domains in government and automatically acquiring semantically related terms for these aspects from associated policy documents. The second step involves computing citizen sentiments and opinions for the different policy aspects. The third involves updating the ontology with the computed sentiments and the last step involves employing a Bayesian Predictive Process to predict likely citizen opinion for a new proposal (policy) based on information available in the ontology. We provide some background to this work, de-scribe our approach in some detail and discuss the progress made.

Original language	English
Title of host publication	ICEGOV 2016 - Proceedings
Subtitle of host publication	9th International Conference on Theory and Practice of Electronic Governance
Editors	Elsa Estevez, John Bertot, Sehl Mellouli
Publisher	Association for Computing Machinery
Pages	27-30
Number of pages	4
ISBN (Electronic)	9781450336406
DOIs	https://doi.org/10.1145/2910019.2910093
Publication status	Published - 1 Mar 2016
Externally published	Yes
Event	9th International Conference on Theory and Practice of Electronic Governance, ICEGOV 2016 - Montevideo, Uruguay Duration: 1 Mar 2016 → 3 Mar 2016

Publication series

Name	ACM International Conference Proceeding Series
Volume	01-03-March-2016

Conference

Conference	9th International Conference on Theory and Practice of Electronic Governance, ICEGOV 2016
Country/Territory	Uruguay
City	Montevideo
Period	1/03/16 → 3/03/16

Keywords

Bayesian policy acceptance prediction
Citizen satisfaction
Decision analytics
Government Decision Support
Opinion mining
Policy aspects
Semantic relatedness
Sentiment analysis

Access to Document

10.1145/2910019.2910093

Cite this

Rezk, M. A., El Khayat, G. A., Ojo, A., & Hussein, S. (2016). A government decision analytics framework based on citizen opinion. In E. Estevez, J. Bertot, & S. Mellouli (Eds.), ICEGOV 2016 - Proceedings: 9th International Conference on Theory and Practice of Electronic Governance (pp. 27-30). (ACM International Conference Proceeding Series; Vol. 01-03-March-2016). Association for Computing Machinery. https://doi.org/10.1145/2910019.2910093

Rezk, Mohamed Adel ; El Khayat, Ghada A. ; Ojo, Adegboyega et al. / A government decision analytics framework based on citizen opinion. ICEGOV 2016 - Proceedings: 9th International Conference on Theory and Practice of Electronic Governance. editor / Elsa Estevez ; John Bertot ; Sehl Mellouli. Association for Computing Machinery, 2016. pp. 27-30 (ACM International Conference Proceeding Series).

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title = "A government decision analytics framework based on citizen opinion",

abstract = "This ongoing research aims to develop a Government Decision Support Framework that employs citizen opinions and sentiments to predict the level of acceptance of newly proposed policies. The system relies on a knowledge base of citizen opinions and an Ontological Model comprising aspects and related terms of different policy domains as an input and a Bayesian predictive procedure. The work proceeds in four basic steps. The first step involves developing domain models comprising aspects for different policy domains in government and automatically acquiring semantically related terms for these aspects from associated policy documents. The second step involves computing citizen sentiments and opinions for the different policy aspects. The third involves updating the ontology with the computed sentiments and the last step involves employing a Bayesian Predictive Process to predict likely citizen opinion for a new proposal (policy) based on information available in the ontology. We provide some background to this work, de-scribe our approach in some detail and discuss the progress made.",

keywords = "Bayesian policy acceptance prediction, Citizen satisfaction, Decision analytics, Government Decision Support, Opinion mining, Policy aspects, Semantic relatedness, Sentiment analysis",

author = "Rezk, \{Mohamed Adel\} and \{El Khayat\}, \{Ghada A.\} and Adegboyega Ojo and Safaa Hussein",

note = "Publisher Copyright: Copyright is held by the owner/author(s).; 9th International Conference on Theory and Practice of Electronic Governance, ICEGOV 2016 ; Conference date: 01-03-2016 Through 03-03-2016",

year = "2016",

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doi = "10.1145/2910019.2910093",

language = "English",

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Rezk, MA, El Khayat, GA, Ojo, A & Hussein, S 2016, A government decision analytics framework based on citizen opinion. in E Estevez, J Bertot & S Mellouli (eds), ICEGOV 2016 - Proceedings: 9th International Conference on Theory and Practice of Electronic Governance. ACM International Conference Proceeding Series, vol. 01-03-March-2016, Association for Computing Machinery, pp. 27-30, 9th International Conference on Theory and Practice of Electronic Governance, ICEGOV 2016, Montevideo, Uruguay, 1/03/16. https://doi.org/10.1145/2910019.2910093

A government decision analytics framework based on citizen opinion. / Rezk, Mohamed Adel; El Khayat, Ghada A.; Ojo, Adegboyega et al.
ICEGOV 2016 - Proceedings: 9th International Conference on Theory and Practice of Electronic Governance. ed. / Elsa Estevez; John Bertot; Sehl Mellouli. Association for Computing Machinery, 2016. p. 27-30 (ACM International Conference Proceeding Series; Vol. 01-03-March-2016).

Research output: Chapter in Book or Conference Publication/Proceeding › Conference Publication › peer-review

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PY - 2016/3/1

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AB - This ongoing research aims to develop a Government Decision Support Framework that employs citizen opinions and sentiments to predict the level of acceptance of newly proposed policies. The system relies on a knowledge base of citizen opinions and an Ontological Model comprising aspects and related terms of different policy domains as an input and a Bayesian predictive procedure. The work proceeds in four basic steps. The first step involves developing domain models comprising aspects for different policy domains in government and automatically acquiring semantically related terms for these aspects from associated policy documents. The second step involves computing citizen sentiments and opinions for the different policy aspects. The third involves updating the ontology with the computed sentiments and the last step involves employing a Bayesian Predictive Process to predict likely citizen opinion for a new proposal (policy) based on information available in the ontology. We provide some background to this work, de-scribe our approach in some detail and discuss the progress made.

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Rezk MA, El Khayat GA, Ojo A, Hussein S. A government decision analytics framework based on citizen opinion. In Estevez E, Bertot J, Mellouli S, editors, ICEGOV 2016 - Proceedings: 9th International Conference on Theory and Practice of Electronic Governance. Association for Computing Machinery. 2016. p. 27-30. (ACM International Conference Proceeding Series). doi: 10.1145/2910019.2910093

A government decision analytics framework based on citizen opinion

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Keywords

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