Robert Beverly, Mark Allman. Findings and Implications from Data Mining the IMC Review Process, ACM SIGCOMM Computer Communication Review, 43(1), January 2013.
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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.

BibTeX:

@article{BA13,
    author  =        "Robert Beverly and Mark Allman",
    title   =        "{Findings and Implications from Data Mining the IMC Review Process}",
    journal =        "ACM Computer Communication Review",
    year    =        2013,
    volume  =        43,
    number  =        1,
    month   =        jan,
}