Scientometrics: Untangling the topics
Digital Libraries
2014-11-13 v2 Social and Information Networks
Data Analysis, Statistics and Probability
Physics and Society
Abstract
Measuring science is based on comparing articles to similar others. However, keyword-based groups of thematically similar articles are dominantly small. These small sizes keep the statistical errors of comparisons high. With the growing availability of bibliographic data such statistical errors can be reduced by merging methods of thematic grouping, citation networks and keyword co-usage.
Cite
@article{arxiv.1403.2140,
title = {Scientometrics: Untangling the topics},
author = {Adam Szanto-Varnagy and Peter Pollner and Tamas Vicsek and Illes J. Farkas},
journal= {arXiv preprint arXiv:1403.2140},
year = {2014}
}
Comments
2 pages, 2 figures