论文标题
科学期刊中论文数量的重型分布
Heavy-Tailed Distribution of the Number of Papers within Scientific Journals
论文作者
论文摘要
学术出版物至少代表了研究科学界作为社会群体的两个好处。首先，他们证明了科学家（合作，指导，遗产等）之间的某种形式的关系，可用于确定和分析社会亚组。其次，其中大多数记录在大型数据库中，易于访问，并包括许多相关信息，从而简化了科学界的定量和定性研究。理解推动一般知识创造的潜在动态，尤其是科学出版物可以通过确定科学的好和坏实践来有助于维持高水平的研究。在本文中，我们旨在通过对同行评审期刊中出版的统计分析来提高这种理解。也就是说，我们表明，作者在给定期刊上发表的论文数量的分布是重尾，但比权力法更轻。有趣的是，我们（通过分析和数值）证明了这种分布与修改后的优先附件过程的结果相匹配，在Barabási-Albert流程之上，我们考虑了有限的科学家职业生涯。
Scholarly publications represent at least two benefits for the study of the scientific community as a social group. First, they attest of some form of relation between scientists (collaborations, mentoring, heritage,...), useful to determine and analyze social subgroups. Second, most of them are recorded in large data bases, easily accessible and including a lot of pertinent information, easing the quantitative and qualitative study of the scientific community. Understanding the underlying dynamics driving the creation of knowledge in general, and of scientific publication in particular can contribute to maintaining a high level of research, by identifying good and bad practices in science. In this article, we aim at advancing this understanding by a statistical analysis of publication within peer-reviewed journals. Namely, we show that the distribution of the number of papers published by an author in a given journal is heavy-tailed, but has lighter tail than a power law. Interestingly, we demonstrate (both analytically and numerically) that such distributions match the result of an modified preferential attachment process, where, on top of a Barabási-Albert process, we take finite career span of scientists into account.
