Paper Accepted at AINA 2024

Trustworthiness of X Users: A One-Class Classification Approach
Trustworthiness of X Users: A One-Class Classification Approach

Trustworthiness of X Users: A One-Class Classification Approach
Trustworthiness of X Users: A One-Class Classification Approach

Title: Trustworthiness of X Users: A One-Class Classification Approach
Authors:Tanveer Khan, Fahad Sohrab, Antonis Michalas and Moncef Gabbouj
Research Artifact: CODE, DATASET
Venue: Proceedings of the 38th International Conference on Advanced Information Networking and Applications (AINA-2024), 19—17 April, 2024, Kitakyushu, Japan


Abstract: X (formerly Twitter) is a prominent online social media platform that plays an important role in sharing information making the content generated on this platform a valuable source of information. Ensuring trust on X is essential to determine the user credibility and prevents issues across various domains. While assigning credibility to X users and classifying them as trusted or untrusted is commonly carried out using traditional machine learning models, there is limited exploration about the use of One-Class Classification (OCC) models for this purpose. In this study, we use various OCC models for X user classification. Additionally, we propose using a subspace-learning-based approach that simultaneously optimizes both the subspace and data description for OCC. We also introduce a novel regularization term for Subspace Support Vector Data Description (SSVDD), expressing data concentration in a lower-dimensional subspace that captures diverse graph structures. Experimental results show superior performance of the introduced regularization term for SSVDD compared to baseline models and state-of-the-art techniques for X user classification.

Tanveer Khan

Tanveer Khan

  • Doctoral Researcher
  • Faculty of Information Technology and Communication Sciences
  • Tampere University
  • +358505969006
  • tanveer.khan@tuni.fi
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Fahad Sohrab

  • Postdoctoral Research Fellow
  • Faculty of Information Technology and Communication Sciences
  • Tampere University
  • +358504731085
  • fahad.sohrab@tuni.fi
Antonios Michalas

Antonios Michalas

  • Associate Professor (tenure track)
  • Cyber security
  • Faculty of Information Technology and Communication Sciences
  • Tampere University
  • +358504478399
  • antonios.michalas@tuni.fi
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Moncef Gabbouj

  • Professor
  • Signal Processing
  • Faculty of Information Technology and Communication Sciences
  • Tampere University
  • +358400736613
  • moncef.gabbouj@tuni.fi
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