Name
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2427036.2427040 | Computer Communication Review |
Keywords | Field | DocType |
recent top-tier computer network,computer science method,call-for-paper adherence,imc review process,computer science review process,topical bias,common hypothesis,initial exploration,computer science research paper,hypothesize review process method,review process | Transparency (graphic),Data mining,Review article,Computer science,Citation,Readability | Journal |
Volume | Issue | ISSN |
43 | 1 | 0146-4833 |
Citations | PageRank | References |
1 | 0.36 | 11 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robert Beverly | 1 | 361 | 32.92 |
| Mark Allman | 2 | 3045 | 278.07 |