Open AccessGenealogical Trees of Scientific Papers
Author(s) -
Michaël Waumans,
Hugues Bersini
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0150588
Subject(s) - popularity , perspective (graphical) , citation , trace (psycholinguistics) , family tree , computer science , data science , citation analysis , bibliometrics , degree (music) , field (mathematics) , genealogy , demography , history , library science , mathematics , sociology , artificial intelligence , psychology , social psychology , linguistics , philosophy , physics , acoustics , pure mathematics
Many results have been obtained when studying scientific papers citations databases in a network perspective. Articles can be ranked according to their current in-degree and their future popularity or citation counts can even be predicted. The dynamical properties of such networks and the observation of the time evolution of their nodes started more recently. This work adopts an evolutionary perspective and proposes an original algorithm for the construction of genealogical trees of scientific papers on the basis of their citation count evolution in time. The fitness of a paper now amounts to its in-degree growing trend and a “dying” paper will suddenly see this trend declining in time. It will give birth and be taken over by some of its most prevalent citing “offspring”. Practically, this might be used to trace the successive published milestones of a research field.