Big Social Data Analytics: A Model for the Public Sector
dc.contributor.advisor | Kamala, Mumtaz A. | |
dc.contributor.advisor | Tassabehji, Rana | |
dc.contributor.author | Bin Saip, Mohamed A. | |
dc.date.accessioned | 2021-02-18T11:34:29Z | |
dc.date.available | 2021-02-18T11:34:29Z | |
dc.date.issued | 2019 | |
dc.identifier.uri | http://hdl.handle.net/10454/18352 | |
dc.description.abstract | The influence of Information and Communication Technologies (ICTs) particularly internet technology has had a fundamental impact on the way government is administered, provides services and interacts with citizens. Currently, the use of social media is no longer limited to informal environments but is an increasingly important medium of communication between citizens and governments. The extensive and increasing use of social media will continue to generate huge amounts of user-generated content known as Big Social Data (BSD). The growing body of BSD presents innumerable opportunities as well as challenges for local government planning, management and delivery of public services to citizens. However, the governments have not yet utilised the potential of BSD for better understanding the public and gaining new insights from this new way of interactions. Some of the reasons are lacking in the mechanism and guidance to analyse this new format of data. Thus, the aim of this study is to evaluate how the body of BSD can be mined, analysed and applied in the context of local government in the UK. The objective is to develop a Big Social Data Analytics (BSDA) model that can be applied in the case of local government. Data generated from social media over a year were collected, collated and analysed using a range of social media analytics and network analysis tools and techniques. The final BSDA model was applied to a local council case to evaluate its impact in real practice. This study allows to better understand the methods of analysing the BSD in the public sector and extend the literature related to e-government, social media, and social network theory | en_US |
dc.description.sponsorship | Universiti Utara Malaysia | en_US |
dc.language.iso | en | en_US |
dc.rights | <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>. | eng |
dc.subject | Big social data | en_US |
dc.subject | Public sector | en_US |
dc.subject | Social network theory | en_US |
dc.subject | Social network analysis | en_US |
dc.subject | Content analysis | en_US |
dc.subject | Sentiment analysis | en_US |
dc.subject | Local government | en_US |
dc.subject | e-Government | en_US |
dc.title | Big Social Data Analytics: A Model for the Public Sector | en_US |
dc.type.qualificationlevel | doctoral | en_US |
dc.publisher.institution | University of Bradford | eng |
dc.publisher.department | Faculty of Engineering and Informatics | en_US |
dc.type | Thesis | eng |
dc.type.qualificationname | PhD | en_US |
dc.date.awarded | 2019 | |
refterms.dateFOA | 2021-02-18T11:34:51Z |