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Computer Science conference best paper selections significantly outperform random chance, with selected papers receiving more citations. This indicates effective peer review in identifying high-impact research.

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Area of Science:

  • Computer Science
  • Bibliometrics
  • Scholarly Communication

Background:

  • Peer evaluation is fundamental to scientific assessment.
  • Pre-publication selection of best papers in Computer Science (CS) conferences is a form of peer evaluation.
  • This study investigates if these selected papers achieve higher citation counts than non-selected papers.

Purpose of the Study:

  • To determine if the selection of
  • best papers
  • in Computer Science conferences predicts higher future citations compared to random selection.
  • To assess if there's a temporal "propaganda effect" influencing these selections.

Main Methods:

  • Collected citation data from Scopus and Google Scholar for best and non-best papers across multiple CS conferences.
  • Calculated the proportion of best papers receiving more citations than non-best papers.
  • Analyzed citation data for pre- and post-2010 periods and determined the proportion of best papers in the top 10% and 20% most cited.

Main Results:

  • Best papers were cited more often than non-best papers with probabilities of 0.72 (Scopus) and 0.78 (Scholar).
  • No significant changes in citation advantage were observed over time.
  • 51% of best papers ranked in the top 10% and 64% in the top 20% of citations within their respective conferences.

Conclusions:

  • Computer Science conference best paper selection processes are demonstrably better than random.
  • A substantial proportion of selected best papers achieve high citation impact.
  • These findings support the efficacy of peer review in identifying influential CS research.