1 INTRODUCTION

2 RELATED WORK, METHODOLOGY AND GENERAL SET-UP

3 MOTIVATION FOR RESEARCH ON FAIRNESS FOR GRAPHS

4 EVALUATION METRICS FOR FAIRNESS

5 REPAIRING BIAS AT THE ORIGIN

6 LEARNING FAIR NODE EMBEDDING

7 POST-PROCESSING APPROACHES

8 BENCHMARK GRAPHS

9 OPEN CHALLENGES