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Fifty shades of grey hat: A socio-psychological analysis of conversations on hacking forums.

McAlaney, J., Kimpton, E. and Thackeray, H, 2019. Fifty shades of grey hat: A socio-psychological analysis of conversations on hacking forums. In: CyPsy24: Annual CyberPsychology, CyberTherapy & Social Networking Conference, 24-26 June 2019, Norfolk, VA, USA.

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Abstract

There remains a lack of understanding as to what determines the path which a young person takes when they first engage with computers and hacking. This research sought to address that gap by exploring the conversations that take place on hacking forums and subreddits. Text in hacking related threads was collected from these sites over the summer period of 2018. Linguistic Inquiry and Word Count (LIWC) software was used to determine the linguistic characteristics of each forum/ subreddit. Thematic analysis was then conducted on a sub-set of text from each source. The results of the LIWC analysis indicated that there are variations in several psychologically relevant factors between these forums and subreddits, including the degree to which users used language that indicated they were being honest, confident, analytical and emotional. There were several results that were inconsistent with stereotypes of hackers, such as a relative absence of language indicating anger. The thematic analysis identified several themes relating to knowledge, skills acquisition, honesty legality and risk. Overall this research demonstrates that there exists an established online community of hackers, which are likely to be encountered by any young person who becomes interested in cybersecurity and hacking. These communities may potentially act as an important source of social support and social identity for their members. Understanding the dynamics of these communities may better help us steer people towards legitimate cybersecurity careers, where their passion and skills can be used for societal good.

Item Type:Conference or Workshop Item (Paper)
Group:Faculty of Science & Technology
ID Code:32495
Deposited By: Symplectic RT2
Deposited On:08 Jul 2019 09:58
Last Modified:14 Mar 2022 14:16

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