Current research on users` perspectives of cyber security and privacy related to traditional and smart devices at home is very active, but the focus is often more on specific modern devices such as mobile and smart IoT devices in a home context. In addition, most were based on smaller-scale empirical studies such as online surveys and interviews. We endeavour to fill these research gaps by conducting a larger-scale study based on a real-world dataset of 413,985 tweets posted by non-expert users on Twitter in six months of three consecutive years (January and February in 2019, 2020 and 2021). Two machine learning-based classifiers were developed to identify the 413,985 tweets. We analysed this dataset to understand non-expert users` cyber security and privacy perspectives, including the yearly trend and the impact of the COVID-19 pandemic. We applied topic modelling, sentiment analysis and qualitative analysis of selected tweets in the dataset, leading to various interesting findings. For instance, we observed a 54% increase in non-expert users` tweets on cyber security and/or privacy related topics in 2021, compared to before the start of global COVID-19 lockdowns (January 2019 to February 2020). We also observed an increased level of help-seeking tweets during the COVID-19 pandemic. Our analysis revealed a diverse range of topics discussed by non-expert users across the three years, including VPNs, Wi-Fi, smartphones, laptops, smart home devices, financial security, and security and privacy issues involving different stakeholders. Overall negative sentiment was observed across almost all topics non-expert users discussed on Twitter 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 different facets of such perspectives.
翻译:目前对用户的网络安全和隐私观点的研究非常活跃,但重点往往更多地放在特定现代设备上,如家庭背景下的移动和智能 IoT 设备;此外,大多数基于小规模的经验研究,如在线调查和访谈;我们努力填补这些研究差距,方法是根据真实世界数据集,非专家用户在连续3年连续6个月(2019年、2020年和2021年的1月和2月)在Twitter上张贴413 985个推文;开发了两个基于机器的叙级工具,以查明413 985个推文;我们分析了这一数据集,以了解非专家用户的网络安全和隐私视角,包括每年的趋势和COVI-19大流行病的影响;我们在数据集中应用了专题建模、情绪分析和对部分推文的定性分析,导致各种有趣的发现;例如,在2021年,非专家用户的网络安全和/或隐私相关议题上的推特增加了54%;在2021年,我们开始开始的OVI-19进行关于网络安全视角,在2019年中也观察到了我们的安全视角。