Twitter User Sentiments Analysis: Health System Cyberattacks Case Study

Muhammad Abusaqer, M. Benaoumeur Senouci*, Kenneth Magel

*Kontaktforfatter

Publikation: Kapitel i bog/rapport/konference-proceedingKonferencebidrag i proceedingsForskning

Abstract

Social media, such as Twitter, allow people to interact with ongoing events and share their sentiments. Therefore, people use social media to report and express their emotions about events they are experiencing. Furthermore, some officials take advantage of the popularity of social media to keep the public informed, especially during emergent events. Researchers have covered sentiment analysis on Twitter in many fields, such as movie reviews, stocks, politics, health, and sports. However, there is a research gap in studying the public's concerns on social media when a cybersecurity breach occurs and how people's sentiment changes over time. To fill the gap, The researchers selected the cyberattacks against Universal Health Services (UHS) during the late days of September 2020 and collected a large dataset of related tweets over five weeks. Live-streaming tweets and historical ones both were compiled. The focus while gathering tweets was in the context of cyberattacks on UHS using keywords and hashtags such as Universal Health System, UHS cyberattack, UHS Ransome, UHS security breach, and UHS locked. Then, the researchers determined tweets' sentiment classification on this developing event using deep learning of Long Short-Term Memory (LSTM) and Artificial Neural Networks (ANN) and their accuracies. Furthermore, the researchers performed exploratory data analysis for the dataset supplying information about how sentiment has changed over time to compare the sentiment per week since the start of these cyberattacks on UHS. This study is the first to provide an analysis of the public's sentiment toward a significant cybersecurity breach on a healthcare provider dealing with COVID-19 based on a large-scale dataset extracted from social media feeds.

OriginalsprogEngelsk
Titel2023 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)
ForlagIEEE
Publikationsdato2023
Sider18-24
ISBN (Trykt)9781665456463
ISBN (Elektronisk)9781665456456
DOI
StatusUdgivet - 2023
Begivenhed5th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2023 - Virtual, Online, Indonesien
Varighed: 20. feb. 202323. feb. 2023

Konference

Konference5th International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2023
Land/OmrådeIndonesien
ByVirtual, Online
Periode20/02/202323/02/2023
NavnInternational Conference on Artificial Intelligence in Information and Communication (ICAIIC)
ISSN2831-6991

Bibliografisk note

Publisher Copyright:
© 2023 IEEE.

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