Findings and Implications from Data Mining the IMC Review Process
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Authors
Beverly, Robert
Allman, Mark
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Date of Issue
2013
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Association for Computing Machinery (ACM)
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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.
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Article
Description
ACM SIGCOMM Computer Communications Review (CCR), January 2013.
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Computer Science (CS)
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.