Login (DCU Staff Only)
Login (DCU Staff Only)

DORAS | DCU Research Repository

Explore open access research and scholarly works from DCU

Advanced Search

Irish attitudes toward COVID tracker app & privacy: sentiment analysis on Twitter and survey data

Lohar, Pintu orcid logoORCID: 0000-0002-5328-1585, Xie, Guodong orcid logoORCID: 0000-0003-0037-8495, Bendechache, Malika orcid logoORCID: 0000-0003-0069-1860, Brennan, Rob orcid logoORCID: 0000-0001-8236-362X, Celeste, Edoardo orcid logoORCID: 0000-0003-1984-4142, Trestian, Ramona orcid logoORCID: 0000-0003-3315-3081 and Tal, Irina orcid logoORCID: 0000-0001-9656-668X (2021) Irish attitudes toward COVID tracker app & privacy: sentiment analysis on Twitter and survey data. In: ARES 2021: The 16th International Conference on Availability, Reliability and Security, 17 - 20 Aug 2021, Vienna Austria. ISBN 978-1-4503-9051

Abstract
Contact tracing apps used in tracing and mitigating the spread of COVID-19 have sparked discussions and controversies worldwide. The major concerns in relation to these apps are around privacy. Ireland was in general praised for the design of its COVID tracker app, and the transparency through which privacy issues were addressed. However, the ”voice” of the Irish public was not really heard or analysed. This study aimed to analyse the Irish public sentiment towards privacy and COVID tracker app. For this purpose we have conducted sentiment analysis on Twitter data collected from public Twitter accounts from Republic of Ireland. We collected COVID-19 related tweets generated in Ireland over a period of time from January 1, 2020 up to December 31, 2020 in order to perform sentiment analysis on this data set. Moreover, the study performed sentiment analysis on the feedback received from a national survey on privacy conducted in Republic of Ireland. The findings of the study reveal a significant criticism towards the app that relate to privacy concerns, but other aspects of the app as well. The findings also reveal some positive attitude towards the fight against COVID-19, but these are not necessarily related to the technological solutions employed for this purpose. The findings of the study contributed to the formulation of useful recommendations communicated to the relevant Irish actors.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:privacy; Sentiment Analysis; COVID-19; tracker app
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > Lero: The Irish Software Engineering Research Centre
Research Initiatives and Centres > ADAPT
Published in: ARES 2021: The 16th International Conference on Availability, Reliability and Security, Proceedings. . Association for Computing Machinery (ACM). ISBN 978-1-4503-9051
Publisher:Association for Computing Machinery (ACM)
Official URL:https://dx.doi.org/10.1145/3465481.3469193
Copyright Information:© 2021 The Authors. Open Access (CC-BY 4.0)
Funders:Science Foundation Ireland through COVID RapidResponseprogrammegrantnumber20/COV/0229andthrough the grant 13/RC/2094 co-funded under the European Regional Development Fund through the Southern and Eastern Regional Operational Programme to Lero- the Irish
ID Code:27573
Deposited On:16 Aug 2022 16:04 by Thomas Murtagh . Last Modified 19 Sep 2023 08:47
Documents

Full text available as:

[thumbnail of 3465481.3469193.pdf]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Creative Commons: Attribution-Noncommercial 3.0
937kB
Downloads

Downloads

Downloads per month over past year

Archive Staff Only: edit this record