Panagiotis Soustas
Year 3 Student – 2022 Intake – Cohort 4 My background is in Computational Linguistics a sub field of Linguistics and Natural Language Processing, which combines Machine Learning and Computational Linguistics, that can have various applications in cross domain research. Linguistic classifiers and their applications are my main research interest. Looking from the scope of Cybersecurity data gathered from criminal communities that reflect on motivations, methods, tactics and potential targets if processed by a linguistic aspect could be used to detect and classify threats and illegal activities. |
|
PhD Project |
Linguistic Anomaly Detection This thesis focuses on the role of linguistic abnormalities as an identifier of malicious or misplaced online content, focusing specifically on the pervasive issue known as Elsagate. This phenomenon, witnessed on popular online video-sharing platforms, such as YouTube, entails the presence of inappropriate or disturbing content within ostensibly harmless children's videos. There are early indications that the pattern of commentary around these videos may be distinctive.
Supervisors: Dr Matthew Edwards (Bristol) Dr Claudia Peersman (Bristol) |
PhD Poster |
|
Year 1 Academic and Industry Placements |
Industrial Placement: Data-driven investigations / Dutch High Tech Crime Unit |
Personal Research Websites |
|
Social Media |
https://www.linkedin.com/in/panagiotis-soustas/
|