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Theory Meets Empiry: A Citation Network Analysis

机译:理论遇上经验:引文网络分析

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摘要

According to a recent survey, ecologists and evolutionary biologists feel that theoretical and empirical research should coexist in a tight feedback loop but believe that the two domains actually interact very little. We evaluate this perception using a citation network analysis for two data sets, representing the literature on sexual selection and speciation. Overall, 54%–60% of citations come from a paper's own category, whereas 17%–23% are citations across categories. These cross-citations tend to focus on highly cited papers, and we observe a positive correlation between the numbers of citations a study receives within and across categories. We find evidence that reviews can function as integrators between the two literatures, argue that theoretical models are analogous to specific empirical study systems, and complement our analyses by studying a cocitation network. We conclude that theoretical and empirical research are more tightly connected than generally thought but that avenues exist to further increase this integration.
机译:根据最近的一项调查,生态学家和进化生物学家认为,理论研究和实证研究应该在紧密的反馈回路中共存,但是他们认为这两个领域实际上相互作用很小。我们使用两个数据集的引用网络分析来评估这种感知,这两个数据集代表有关性选择和物种形成的文献。总体而言,有54%–60%的引用来自论文自己的类别,而17%–23%是来自不同类别的引用。这些交叉引用往往集中在被高引用的论文上,并且我们观察到一项研究在类别内和类别之间获得的引用数量之间存在正相关。我们发现证据表明评论可以作为两种文献之间的整合者,认为理论模型类似于特定的经验研究系统,并通过研究引文网络来补充我们的分析。我们得出的结论是,理论和实证研究之间的联系比一般人认为的要紧密得多,但是存在进一步增加这种整合的途径。

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