Findings and Implications from Data Mining the IMC Review Process

TitleFindings and Implications from Data Mining the IMC Review Process
Publication TypeJournal Article
Year of Publication2013
AuthorsBeverly, R., & Allman M.
Published inACM SIGCOMM Computer Communication Review
Volume3
Issue1
Page(s)23-29
Other Numbers3410
Abstract

The computer science research paper review process is largely human and time-intensive. More worrisome, review processes are frequently questioned, and often non-transparent. This work advocates applying computer science methods and tools to the computer science review process. As an initial exploration, we data mine the submissions, bids, reviews, and decisions from a recent top-tier computer networking conference. We empirically test several common hypotheses, including the existence of readability, citation, call-for-paper adherence, and topical bias. From our findings, we hypothesize review process methods to improve fairness, efficiency, and transparency.

URLhttp://www.icsi.berkeley.edu/pubs/networking/findingsimplications12.pdf
Bibliographic Notes

ACM SIGCOMM Computer Communication Review, Vol. 3, No. 1, pp. 23-29

Abbreviated Authors

R. Beverly and M. Allman

ICSI Research Group

Networking and Security

ICSI Publication Type

Article in journal or magazine