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.
|Number of pages||7|
|Journal||CEUR Workshop Proceedings|
|Publication status||Published - 2017|
|Event||2nd Workshop on Mining Scientific Papers: Computational Linguistics and Bibliometrics, CLBib 2017 - Wuhan, China|
Duration: 2017 Oct 16 → …
Bibliographical noteFunding Information:
The work is supported by the National Science Foundation (Award Number: 1633286). We thank Zhipeng Zheng at Department of Chemistry, University of Pennsylvania for his help in the xemplae nierprettation.
All Science Journal Classification (ASJC) codes
- Computer Science(all)