This project is about exploring whether there is a bias in citations for women and minority groups. Recent study shows that some papers do not receive citations as it would be expected from their relevance (e.g. co-citation patterns). These results suggest that there is a tendency for authors to discriminate among relevant papers. This can have an impact on the reputation of the paper and the author. In addition, some studies showed that women are less likely to receive citations. However, the effect of gender or nationality has not fully explored and normally previous findings are not based on statistical significant testing.
In this project, the student uses statistical significant testing similar to , to study the pattern of citations to explore gender differences and ethnicity differences. The dataset is American Physical Society dataset that consist of all citation records in this corpus for the last 50 years. From the previous analysis we can extract the gender of the authors and the ethnic background is determined by the faculty information.