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Content and interaction-based mapping of Reddit posts related to information security

Author

Listed:
  • Konstantinos Charmanas

    (Aristotle University of Thessaloniki)

  • Nikolaos Mittas

    (Democritus University of Thrace)

  • Lefteris Angelis

    (Aristotle University of Thessaloniki)

Abstract

Ensuring the privacy and safety of platform users has become a complex objective due to the emerging threats that surround any type of network, software, and hardware. Scams, malwares, hackers, and security vulnerabilities form the epicenter of cyber threats causing severe damage to the affected systems and sensitive data of users. Thus, users turn to online social networks to report cyber threats, discuss topics of their interest, and obtain knowledge concerning the various perspectives of information security. In this study, we aim to address the concepts of social interactions surrounding information security-related content by retrieving and analyzing Reddit posts from 45 relevant subreddits. In this regard, a word clustering approach is employed, based on the Affinity Propagation algorithm, that leads to the extraction and interpretation of 54 concepts. These concepts are relevant to information security and some more generic areas of interest including social media, software vendors, and labors. Furthermore, to provide a more comprehensive overview of users’ activity in the different Reddit communities/subreddits, a knowledge map associating subreddits and concepts based on their conceptual similarities is also established. The analysis shows that the descriptions of the examined subreddits are strongly related to their underlying concepts. At the same time, the outcomes also assess the conceptual associations between the different subreddits, offering knowledge related to similar and distant communities. Ultimately, two post metrics are utilized to explore how the concepts may impact user interactions. This allows us to differentiate between concepts associated with posts typically endorsed by communities, resulting in increased information exchange (via comments), or contributing as news/announcements. Overall, the findings of this study can be used as a knowledge basis in determining user interests, opinions, perspectives, and responsiveness, when it comes to cyber threats, attacks, and malicious activities. Also, the respective outcomes can contribute as a guide for identifying similar communities/subreddits and themes. Regarding the methodological contributions of this study, the proposed framework can be adapted to similar datasets and research goals as it does not depend on the special characteristics of the imported data, offering, in turn, a practical approach for future research.

Suggested Citation

  • Konstantinos Charmanas & Nikolaos Mittas & Lefteris Angelis, 2024. "Content and interaction-based mapping of Reddit posts related to information security," Journal of Computational Social Science, Springer, vol. 7(2), pages 1187-1222, October.
    • Handle: RePEc:spr:jcsosc:v:7:y:2024:i:2:d:10.1007_s42001-024-00269-4
    DOI: 10.1007/s42001-024-00269-4
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    References listed on IDEAS

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    1. Jasser Jasser & Ivan Garibay & Steve Scheinert & Alexander V. Mantzaris, 2022. "Controversial information spreads faster and further than non-controversial information in Reddit," Journal of Computational Social Science, Springer, vol. 5(1), pages 111-122, May.
    2. Nureni Ayofe Azeez & Ahmed Oladapo Lawal & Sanjay Misra & Jonathan Oluranti, 2022. "Machine learning approach for identifying suspicious uniform resource locators (URLs) on Reddit social network," African Journal of Science, Technology, Innovation and Development, Taylor & Francis Journals, vol. 14(6), pages 1618-1626, September.
    3. Muting Wu & Raul Aranovich & Vladimir Filkov, 2021. "Evolution and differentiation of the cybersecurity communities in three social question and answer sites: A mixed-methods analysis," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-30, December.
    4. Prasha Shrestha & Arun Sathanur & Suraj Maharjan & Emily Saldanha & Dustin Arendt & Svitlana Volkova, 2020. "Multiple social platforms reveal actionable signals for software vulnerability awareness: A study of GitHub, Twitter and Reddit," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-28, March.
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