The University of Southampton
University of Southampton Institutional Repository

Towards an understanding of uncertainty on Wikipedia during crises: a mixed methods approach

Towards an understanding of uncertainty on Wikipedia during crises: a mixed methods approach
Towards an understanding of uncertainty on Wikipedia during crises: a mixed methods approach
This thesis proposes an interdisciplinary approach to understanding the Wikipedia editors' response to new disease outbreak crises. A mixed methods triangulation-based approach is used to examine the change in the editing patterns and the response to the uncertainty during new disease outbreak crises on Wikipedia. Quantitative data sources have been utilised to reveal the patterns of editing activities during new disease outbreak crises and to establish the reasons behind this change. Qualitative data sources have been used to distinguish between the forms and the strategies used to manage the uncertainty during new disease outbreak crises. The triangulation and the integration of results revealed Wikipedia as a social machine. This is further discussed while highlighting the importance of 'co-creation' on Wikipedia during new disease outbreak crises. This thesis presents a thematic framework that depicts various forms of uncertainty and the strategies used to manage this uncertainty on Wikipedia during crises. Therefore, this thesis provides a conceptual and methodological contribution to the field of Web Science and has important implications for future research.
University of Southampton
Al Tamime, Reham
bb5c8080-80e5-49ef-b649-c53d08e8c088
Al Tamime, Reham
bb5c8080-80e5-49ef-b649-c53d08e8c088
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c

Al Tamime, Reham (2020) Towards an understanding of uncertainty on Wikipedia during crises: a mixed methods approach. University of Southampton, Doctoral Thesis, 217pp.

Record type: Thesis (Doctoral)

Abstract

This thesis proposes an interdisciplinary approach to understanding the Wikipedia editors' response to new disease outbreak crises. A mixed methods triangulation-based approach is used to examine the change in the editing patterns and the response to the uncertainty during new disease outbreak crises on Wikipedia. Quantitative data sources have been utilised to reveal the patterns of editing activities during new disease outbreak crises and to establish the reasons behind this change. Qualitative data sources have been used to distinguish between the forms and the strategies used to manage the uncertainty during new disease outbreak crises. The triangulation and the integration of results revealed Wikipedia as a social machine. This is further discussed while highlighting the importance of 'co-creation' on Wikipedia during new disease outbreak crises. This thesis presents a thematic framework that depicts various forms of uncertainty and the strategies used to manage this uncertainty on Wikipedia during crises. Therefore, this thesis provides a conceptual and methodological contribution to the field of Web Science and has important implications for future research.

Text
Towards an Understanding of Uncertainty on Wikipedia During Crises: A Mixed Methods Approach - Version of Record
Available under License University of Southampton Thesis Licence.
Download (6MB)

More information

Published date: January 2020

Identifiers

Local EPrints ID: 442084
URI: http://eprints.soton.ac.uk/id/eprint/442084
PURE UUID: c344cde7-a0ea-49d4-8e68-2013d260febc
ORCID for Wendy Hall: ORCID iD orcid.org/0000-0003-4327-7811

Catalogue record

Date deposited: 07 Jul 2020 16:48
Last modified: 13 Dec 2021 02:32

Export record

Contributors

Author: Reham Al Tamime
Thesis advisor: Wendy Hall ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×