Date of Award

5-2019

Document Type

Thesis

Degree Name

Master of Science (MS)

College/School

College of Science and Mathematics

Department/Program

Computer Science

Thesis Sponsor/Dissertation Chair/Project Chair

Aparna Varde

Committee Member

Anna Feldman

Committee Member

Boxiang Dong

Abstract

Smart Governance is an emerging research area which has attracted scientific as well as policy interests, and aims to improve collaboration between government and citizens, as well as other stakeholders. Our project aims to enable lawmakers to incorporate data driven decision making in enacting ordinances. Our first objective is to create a mechanism for mapping ordinances (local laws) and tweets to Smart City Characteristics (SCC). The use of SCC has allowed us to create a mapping between a huge number of ordinances and tweets, and the use of Commonsense Knowledge (CSK) has allowed us to utilize human judgment in mapping.

We have then enhanced the mapping technique to link multiple tweets to SCC. In order to promote transparency in government through increased public participation, we have conducted sentiment analysis of tweets in order to evaluate the opinion of the public with respect to ordinances passed in a particular region.

Our final objective is to develop a mapping algorithm in order to directly relate ordinances to tweets. In order to fulfill this objective, we have developed a mapping technique known as TOLCS (Tweets Ordinance Linkage by Commonsense and Semantics). This technique uses pragmatic aspects in Commonsense Knowledge as well as semantic aspects by domain knowledge. By reducing the sample space of big data to be processed, this method represents an efficient way to accomplish this task.

The ultimate goal of the project is to see how closely a given region is heading towards the concept of Smart City.

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