| Zdroj: |
Panagiotou, A, Ghita, B, Shiaeles, S & Bendiab, K 2019, FaceWallGraph : using machine learning for profiling user behaviour from Facebook Wall . in O Galinina, S Andreev, Y Koucheryavy & S Balandin (eds), Internet of Things, Smart Spaces, and Next Generation Networks and Systems-19th International Conference, NEW2AN 2019, and 12th Conference, ruSMART 2019, Proceedings . Lecture Notes in Computer Science, vol. 11660, Springer, pp. 125-134, 19th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems, NEW2AN 2019, and 12th Conference on Internet of Things and Smart Spaces, ruSMART 2019, St. Petersburg, Russian Federation, 26/08/19 . https://doi.org/10.1007/978-3-030-30859-9_11 |
| Popis: |
Facebook represents the current de-facto choice for social media, changing the nature of social relationships. The increasing amount of personal information that runs through this platform publicly exposes user behaviour and social trends, allowing aggregation of data through conventional intelligence collection techniques such as OSINT (Open Source Intelligence). In this paper, we propose a new method to detect and diagnose variations in overall Facebook user psychology through Open Source Intelligence (OSINT) and machine learning techniques. We are aggregating the spectrum of user sentiments and views by using N-Games charts, which exhibit noticeable variations over time, validated through long term collection. We postulate that the proposed approach can be used by security organisations to understand and evaluate the user psychology, then use the information to predict insider threats or prevent insider attacks. |
