Carnegie Mellon University
Browse
file.pdf (127.71 kB)

Mixed Membership Models of Scientific Publications

Download (127.71 kB)
journal contribution
posted on 1987-01-01, 00:00 authored by Elena Erosheva, Stephen E. Fienberg, John D. Lafferty
The Proceedings of the National Academy of Sciences (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 manuscripts, 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 soft classification 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 well as other features of the data relevant to soft classification

History

Publisher Statement

All Rights Reserved

Date

1987-01-01

Usage metrics

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC