A study of the impact of data sharing on article citations using journal policies as a natural experiment
A study of the impact of data sharing on article citations using journal policies as a natural experiment
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DOI：
10.1371/journal.pone.0225883
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发表时间：
2019-12-18
期刊：
影响因子：
3.7
通讯作者：
Rose, Andrew K.
中科院分区：
文献类型：
--
作者：
Christensen, Garret;Dafoe, Allan;Rose, Andrew K.
这项研究使用期刊政策作为自然实验，估计了数据共享对学术论文引文的影响。我们首先研究了17种高影响力的期刊，这些期刊采取了公开发表文章数据的要求。我们将这17种期刊与13种没有政策变化的期刊进行匹配，发现编辑政策变化前发表的经验性文章的引文率与政策变化后不久发表的文章没有统计学上的显著差异。然后，我们询问这种无效结果是否源于数据共享政策的遵从性较差，并将数据共享政策的变化作为工具变量，更密切地考察两种在新数据政策执行方面相对较强的经济学和政治学领先期刊。我们发现，提供数据的文章被额外引用了97次(估计标准误差为34次)。我们的结论是：a)分享数据的作者最终可能会得到额外的学术引用，以及b)数据发布政策本身并不会增加期刊上发表的文章的影响，除非这些政策得到执行。
This study estimates the effect of data sharing on the citations of academic articles, using journal policies as a natural experiment. We begin by examining 17 high-impact journals that have adopted the requirement that data from published articles be publicly posted. We match these 17 journals to 13 journals without policy changes and find that empirical articles published just before their change in editorial policy have citation rates with no statistically significant difference from those published shortly after the shift. We then ask whether this null result stems from poor compliance with data sharing policies, and use the data sharing policy changes as instrumental variables to examine more closely two leading journals in economics and political science with relatively strong enforcement of new data policies. We find that articles that make their data available receive 97 additional citations (estimate standard error of 34). We conclude that: a) authors who share data may be rewarded eventually with additional scholarly citations, and b) data-posting policies alone do not increase the impact of articles published in a journal unless those policies are enforced.