Cyber Buzz: Examining Virality Characteristics of Cybersecurity Content In Social Networks. (December 2020)

• Record Type: Journal Article
• Authors: Shields, Thomas; Li, Hannah; Lebedev, Peter; Dykstra, Josiah
• Is Part Of: Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Volume 64:Part 1(2020)
• Page Start: 441
• Page End: 445
• Publication Date: 2020-12
• Subjects: Human engineering -- Congresses; 620.8205
• DOI: 10.1177/1071181320641099
• Languages: English
• ISSNs: 1541-9312

Abstract

The Internet is a rich environment for information to spread rapidly and widely. The ability of cybersecurity content to achieve virality in social networks can be useful for measuring security awareness, policy adoption, or cybersecurity literacy. It may also reveal new and emerging cybersecurity events. Virality in online social networks can be characterized and measured many ways and have different causes. Leveraging existing research in social network virality measurements, we calculate and analyze virality measurements and correlations on an anonymized Reddit dataset, examining overall trends and characteristics of individual cybersecurity forums (subreddits). We reproduce content-based virality prediction algorithms and assess their performance, then introduce additional features beyond post title, including time of day, to improve prediction accuracy to ~71% for each of the virality scores. We examine the intersection of the virality facets to reveal correlations about the content and times when cybersecurity content is most viral.