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Perspectives of Non-Expert Users on Cyber Security and Privacy: An Analysis of Online Discussions on Twitter

Pattnaik, Nandita, Li, Shujun, Nurse, Jason R. C. (2022) Perspectives of Non-Expert Users on Cyber Security and Privacy: An Analysis of Online Discussions on Twitter. Computers and Security, . ISSN 0167-4048. (In press) (doi:10.1016/j.cose.2022.103008) (KAR id:96259)

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Official URL:
https://doi.org/10.1016/j.cose.2022.103008

Abstract

Many researchers have studied non-expert users’ perspectives of cyber security and privacy aspects of computing devices at home, but their studies are mostly small-scale empirical studies based on online surveys and interviews and limited to one or a few specific types of devices, such as smart speakers. This paper reports our work on an online social media analysis of a large-scale Twitter dataset, covering cyber security and privacy aspects of many different types of computing devices discussed by non-expert users in the real world. We developed two new machine learning based classifiers to automatically create the Twitter dataset with 435,207 tweets posted by 337,604 non-expert users in January and February of 2019, 2020 and 2021. We analyzed the dataset using both quantitative (topic modeling and sentiment analysis) and qualitative analysis methods, leading to various previously unknown findings. For instance, we observed a sharp (more than doubled) increase of non-expert users’ tweets on cyber security and privacy during the pandemic in 2021, compare to in the pre-COVID years (2019 and 2020). Our analysis revealed a diverse range of topics discussed by non-expert users, including VPNs, Wi-Fi, smartphones, laptops, smart home devices, financial security, help-seeking, and roles of different stakeholders. Overall negative sentiment was observed across almost all topics in all the three years. Our results confirm the multi-faceted nature of non-expert users’ perspectives on cyber security and privacy and call for more holistic, comprehensive and nuanced research on their perspectives.

Item Type: Article
DOI/Identification number: 10.1016/j.cose.2022.103008
Uncontrolled keywords: Cyber security, Privacy, Twitter, User perspectives, Smart home, Smart device, Topic Modelling, Sentiment analysis, Machine learning, Classifier
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Funders: University of Kent (https://ror.org/00xkeyj56)
Depositing User: Nandita Pattnaik
Date Deposited: 20 Nov 2022 12:06 UTC
Last Modified: 21 Nov 2022 15:13 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/96259 (The current URI for this page, for reference purposes)
Pattnaik, Nandita: https://orcid.org/0000-0003-1272-077X
Li, Shujun: https://orcid.org/0000-0001-5628-7328
Nurse, Jason R. C.: https://orcid.org/0000-0003-4118-1680
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