A Survey on Fairness for Machine Learning on Graphs. (arXiv:2205.05396v1 [cs.LG])

Nowadays, the analysis of complex phenomena modeled by graphs plays a crucial
role in many real-world application domains where decisions can have a strong
societal impact. However, numerous studies and papers have recently revealed
that machine learning models could lead to potential disparate treatment
between individuals and unfair outcomes. In that context, algorithmic
contributions for graph mining are not spared by the problem of fairness and
present some specific challenges related to the intrinsic nature of graphs: (1)
graph data …

arxiv fairness graphs learning machine machine learning survey