Topics of Interest

The topics of interest include but are not limited to:

  • Methods to detect and identify different social data biases such as behavioral, content and temporal biases
  • Analyzing and quantifying biases in prototypical processing pipeline for social data
  • Auditing existing social software systems
  • Ethical boundaries, general concepts and principles in social data mining
  • Fairness, accountability and transparency in analyzing social data
  • Privacy and trust consideration in social analytic
  • Evaluation of machine learning and AI frameworks and metrics
  • Explainability and right to explanation in machine learning/ deep learning/AI social mining methods
  • Age of information and social media mining
  • Fairness, accountability and transparency in social media algorithms
  • Bias, fairness in social media applications such recommender systems, target advertising, NLP, etc
  • New datasets and evaluation methodologies to quantify biases in social data