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Peer-selected 'best Papers'-are They Really That 'good'?

机译:同行评选的“最佳论文”-他们真的是“好”人吗?

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摘要

Background Peer evaluation is the cornerstone of science evaluation. In this paper, we analyze whether or not a form of peer evaluation, the pre-publication selection of the best papers in Computer Science (CS) conferences, is better than random, when considering future citations received by the papers. Methods Considering 12 conferences (for several years), we collected the citation counts from Scopus for both the best papers and the non-best papers. For a different set of 17 conferences, we collected the data from Google Scholar. For each data set, we computed the proportion of cases whereby the best paper has more citations. We also compare this proportion for years before 2010 and after to evaluate if there is a propaganda effect. Finally, we count the proportion of best papers that are in the top 10% and 20% most cited for each conference instance. Results The probability that a best paper will receive more citations than a non best paper is 0.72 (95% CI = 0.66, 0.77) for the Scopus data, and 0.78 (95% CI = 0.74, 0.81) for the Scholar data. There are no significant changes in the probabilities for different years. Also, 51% of the best papers are among the top 10% most cited papers in each conference/year, and 64% of them are among the top 20% most cited. Discussion There is strong evidence that the selection of best papers in Computer Science conferences is better than a random selection, and that a significant number of the best papers are among the top cited papers in the conference.
机译:背景同行评估是科学评估的基石。在本文中,当考虑到将来收到的论文引文时,我们分析同行评议的一种形式(计算机科学(CS)会议上最佳论文的出版前选择)比随机抽样更好。方法考虑12个会议(长达数年),我们从Scopus收集了最佳论文和非最佳论文的引用计数。对于其他17个会议,我们从Google Scholar中收集了数据。对于每个数据集,我们计算出最佳论文被引次数更多的案例所占的比例。我们还比较了2010年之前和之后几年的比例,以评估是否有宣传效果。最后,我们计算每个会议实例中被引用次数最多的前10%和20%的最佳论文的比例。结果对于Scopus数据,最佳论文比非最佳论文得到更多引用的概率是0.72(95%CI = 0.66,0.77),而Scholar数据是0.78(95%CI = 0.74,0.81)。不同年份的概率没有显着变化。此外,在每个会议/年度中,被引用的最佳论文中有51%是被引用次数最多的10%论文,而被引用的前20%则是其中的64%。讨论有充分的证据表明,在计算机科学会议上选择最佳论文要好于随机选择,并且在会议中被引用最多的论文中有大量的最佳论文。

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