COVID-19 pandemic & cyber security issues: Sentiment analysis and topic modeling approach

被引:3
|
作者
Khandelwal, Sonal [1 ]
Chaudhary, Aanyaa [1 ]
机构
[1] Manipal Univ Jaipur, TAPMI Sch Business, Jaipur Ajmer Express Highway, Jaipur 303007, Rajasthan, India
关键词
Cyber security; Cyber crime; Sentiment analysis; Topic modeling; Text mining; Big data; Twitter; TWITTER; MANAGEMENT; TRENDS; USAGE;
D O I
10.1080/09720529.2022.2072421
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The purpose of this study is to understand public awareness of cybersecurity-related issues and discussions during the COVID-19 pandemic. Employees and confidential organizational data are vulnerable to cyber-attacks as a result of the pandemic, which has raised concerns about cyber security about the new normal of working from home. The public's main sentiments and aspects related to cyber security concerns have been mined from tweets on the microblogging social media website Twitter. Sentiment Analysis and Topic Modeling techniques have been applied to understand the perspectives, emotions, and themes discussed by people. The analysis reveals people are becoming more aware of cybercrime-related concerns and are more positive than negative in combating the challenge of cybercrime. The paper also highlights the main themes revealed by Topic Modeling.
引用
收藏
页码:987 / 997
页数:11
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