Researchers may describe different aspects of past scientific publications in their publications and the descriptions may keep changing in the evolution of science. The diverse and changing descriptions (i.e., citation context) on a publication characterize the impact and contributions of the past publication.
In this article, we aim to provide an approach to understanding the changing and complex roles of a publication characterized by its citation context. We described a method to represent the publications’ dynamic roles in science community in different periods as a sequence of vectors by training temporal embedding models.
The temporal representations can be used to quantify how much the roles of publications changed and interpret how they changed.
Our study in the biomedical domain shows that our metric on the changes of publications’ roles is stable over time at the population level but significantly distinguish individuals. We also show the interpretability of our methods by a concrete example.
Authors : Zoltán Néda, Levente Varga, Tamás S. Biró
The distribution of scientific citations for publications selected with different rules (author, topic, institution, country, journal, etc.) collapse on a single curve if one plots the citations relative to their mean value.
We find that the distribution of shares for the Facebook posts re-scale in the same manner to the very same curve with scientific citations. This finding suggests that citations are subjected to the same growth mechanism with Facebook popularity measures, being influenced by a statistically similar social environment and selection mechanism.
In a simple master-equation approach the exponential growth of the number of publications and a preferential selection mechanism leads to a Tsallis-Pareto distribution offering an excellent description for the observed statistics.
Based on our model and on the data derived from PubMed we predict that according to the present trend the average citations per scientific publications exponentially relaxes to about 4.
The accumulation of evidence that open access publishing can increase citation rates highlights one benefit of universal accessibility to scholarly works. However, studies investigating the effect of open access publishing on citations are typically conducted across a wide variety of journals and disciplines, introducing a number of potential issues and limiting their utility for specific disciplines.
Here, I used three primary marine ecology journals with an open access option as a “microcosm” of scientific publishing to determine whether or not open access articles received more citations than non-open access articles during the same time frame, controlling for self-citations, article type, and journal impact factor.
I also tested for the effects of time since publication and the number of authors. Citations were positively correlated with time since publication and differed across the three journals. In addition, open access articles received significantly more citations than non-open access articles.
Self-citations increased with author number and were affected by a complex interaction between open access, journal, and time since publication. This study demonstrates that open access articles receive more citations in hybrid marine ecology journals, although the causal factors driving this trend are unknown.
An experiment run in 2009 could not assess whether making monographs available in open access enhanced scholarly impact. This paper revisits the experiment, drawing on additional citation data and tweets. It attempts to answer the following research question: does open access have a positive influence on the number of citations and tweets a monograph receives, taking into account the influence of scholarly field and language?
The correlation between monograph citations and tweets is also investigated. The number of citations and tweets measured in 2014 reveal a slight open access advantage, but the influence of language or subject should also be taken into account. However, Twitter usage and citation behaviour hardly overlap.
Authors : Vincent Larivière, Véronique Kiermer, Catriona J. MacCallum, Marcia McNutt, Mark Patterson, Bernd Pulverer, Sowmya Swaminathan, Stuart Taylor, Stephen Curry
Although the Journal Impact Factor (JIF) is widely acknowledged to be a poor indicator of the quality of individual papers, it is used routinely to evaluate research and researchers. Here, we present a simple method for generating the citation distributions that underlie JIFs.
Application of this straightforward protocol reveals the full extent of the skew of distributions and variation in citations received by published papers that is characteristic of all scientific journals.
Although there are differences among journals across the spectrum of JIFs, the citation distributions overlap extensively, demonstrating that the citation performance of individual papers cannot be inferred from the JIF.
We propose that this methodology be adopted by all journals as a move to greater transparency, one that should help to refocus attention on individual pieces of work and counter the inappropriate usage of JIFs during the process of research assessment.
Authors : Molly M. King, Carl T. Bergstrom, Shelley J. Correll, Jennifer Jacquet, Jevin D. West
How common is self-citation in scholarly publication and does the practice vary by gender? Using novel methods and a dataset of 1.5 million research papers in the scholarly database JSTOR published between 1779-2011, we find that nearly 10% of references are self-citations by a paper’s authors.
We further find that over the years between 1779-2011, men cite their own papers 56% more than women do. In the last two decades of our data, men self-cite 70% more than women. Women are also more than ten percentage points more likely than men to not cite their own previous work at all.
Despite increased representation of women in academia, this gender gap in self-citation rates has remained stable over the last 50 years. We break down self-citation patterns by academic field and number of authors, and comment on potential mechanisms behind these observations.
These findings have important implications for scholarly visibility and likely consequences for academic careers.