论文标题
迈向更现实的引文模型：研究团队规模的关键作用
Towards a more realistic citation model: The key role of research team sizes
论文作者
论文摘要
我们提出了一个新的引用模型，该模型建立在现有模型上，该模型明确或隐式包含“直接”和“间接”（了解引用论文的存在是从另一篇论文中的参考文献中的存在）引用机制。我们的模型偏离了直接引用均匀概率的通常的，不切实际的假设，其中引用的初始差异纯粹是随机的。取而代之的是，我们证明了一种两种机制模型，其中直接引用的可能性与纸张（团队规模）上的作者数量成正比，能够重现天文学领域中发表的文章的经验引文分布，并且在不同的时间点。对我们的模型的解释是，当更多的人非常熟悉某些工作时，将增强固有的引文能力，因此，纸张的最初可见性将得到增强，偏爱大型团队的论文。尽管内在的引文能力不能仅取决于团队的规模，但我们的模型表明，它必须在某种程度上与之相关，并且以类似的方式分发，即具有强力法尾巴。因此，我们的团队大小模型定性地解释了引文数量与论文中的作者数量之间存在相关性。
We propose a new citation model which builds on the existing models that explicitly or implicitly include "direct" and "indirect" (learning about a cited paper's existence from references in another paper) citation mechanisms. Our model departs from the usual, unrealistic assumption of uniform probability of direct citation, in which initial differences in citation arise purely randomly. Instead, we demonstrate that a two-mechanism model in which the probability of direct citation is proportional to the number of authors on a paper (team size) is able to reproduce the empirical citation distributions of articles published in the field of astronomy remarkably well, and at different points in time. Interpretation of our model is that the intrinsic citation capacity, and hence the initial visibility of a paper, will be enhanced when more people are intimately familiar with some work, favoring papers from larger teams. While the intrinsic citation capacity cannot depend only on the team size, our model demonstrates that it must be to some degree correlated with it, and distributed in a similar way, i.e., having a power-law tail. Consequently, our team-size model qualitatively explains the existence of a correlation between the number of citations and the number of authors on a paper.
