Choi, Hao, Downie to present at music information retrieval conference

Stephen Downie
J. Stephen Downie, Professor, Associate Dean for Research, and Co-Director of the HathiTrust Research Center
Yun Hao
Yun Hao

Doctoral students Kahyun Choi and Yun Hao and Professor J. Stephen Downie will present their paper, "WiMIR: An Informetric Study On Women Authors In ISMIR," at the 17th International Society for Music Information Retrieval (ISMIR) Conference. Coauthors of the paper include Xiao Hu (PhD '10), Jin Ha Lee (PhD '08), Audrey Laplante, and Sally Jo Cunningham.

Abstract: The Music Information Retrieval (MIR) community is becoming increasingly aware of a gender imbalance evident in ISMIR participation and publication. This paper reports upon a comprehensive informetric study of the publication, authorship and citation characteristics of female researchers in the context of the ISMIR conferences. All 1,610 papers in the ISMIR proceedings written by 1,910 unique authors from 2000 to 2015 were collected and analyzed. Only 14.1% of all papers were led by female researchers. Temporal analysis shows that the percentage of lead female authors has not improved over the years, but more papers have appeared with female co-authors in very recent years. Topics and citation numbers are also analyzed and compared between female and male authors to identify research emphasis and to measure impact. The results show that the most prolific authors of both genders published similar numbers of ISMIR papers and the citation counts of lead authors in both genders had no significant difference. We also analyzed the collaboration patterns to discover whether gender is related to the number of collaborators. Implications of these findings are discussed and suggestions are proposed on how to continue encouraging and supporting female participation in the MIR field.

The conference—organized by New York University and Columbia University—will take place in New York City from August 7-11. It is the world’s leading research forum on processing, searching, organizing, and accessing music-related data.

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