DMCA
Mixed-membership models of scientific publications (2004)
| Citations: | 133 - 13 self |
BibTeX
@MISC{Erosheva04mixed-membershipmodels,
author = {Elena Erosheva and Stephen Fienberg and John Lafferty},
title = { Mixed-membership models of scientific publications},
year = {2004}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
PNAS is one of world’s most cited multidisciplinary scientific journals. The PNAS official classification structure of subjects is reflected in topic labels submitted by the authors of articles, largely related to traditionally established disciplines. These include broad field classifications into physical sciences, biological sciences, social sciences, and further subtopic classifications within the fields. Focusing on biological sciences, we explore an internal softclassification structure of articles based only on semantic decompositions of abstracts and bibliographies and compare it with the formal discipline classifications. Our model assumes that there is a fixed number of internal categories, each characterized by multinomial distributions over words (in abstracts) and references (in bibliographies). Soft classification for each article is based on proportions of the article’s content coming from each category. We discuss the appropriateness of the model for the PNAS database as
Keyphrases
colloquium mixed-membership model scientific publication biological science soft classification social science internal category article content multinomial distribution topic label subtopic classification internal softclassification structure broad field classification semantic decomposition fixed number formal discipline classification pnas database physical science cited multidisciplinary scientific journal pnas official classification structure
