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Mapping the evolution of scientific fields.

Herrera M, Roberts DC, Gulbahce N - PLoS ONE (2010)

Bottom Line: Two PACS numbers are linked if there exist publications that reference them simultaneously.The communities we identify map to known scientific fields, and their age depends on their size and activity.We expect our approach to quantifying the evolution of ideas to be relevant for making predictions about the future of science and thus help to guide its development.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics and Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland, United States of America.

ABSTRACT
Despite the apparent cross-disciplinary interactions among scientific fields, a formal description of their evolution is lacking. Here we describe a novel approach to study the dynamics and evolution of scientific fields using a network-based analysis. We build an idea network consisting of American Physical Society Physics and Astronomy Classification Scheme (PACS) numbers as nodes representing scientific concepts. Two PACS numbers are linked if there exist publications that reference them simultaneously. We locate scientific fields using a community finding algorithm, and describe the time evolution of these fields over the course of 1985-2006. The communities we identify map to known scientific fields, and their age depends on their size and activity. We expect our approach to quantifying the evolution of ideas to be relevant for making predictions about the future of science and thus help to guide its development.

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The scientific concept network for the first half of 2005.
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pone-0010355-g003: The scientific concept network for the first half of 2005.

Mentions: In order to study the evolution of different fields in physics, one must first find these fields in our network. We hypothesize that scientific fields are represented by communities in our PACS network. These communities are found using the CFinder algorithm, which is based on a clique percolation method [21]. Figs. 2 and 3 present examples of the community structure extracted utilizing CFinder.


Mapping the evolution of scientific fields.

Herrera M, Roberts DC, Gulbahce N - PLoS ONE (2010)

The scientific concept network for the first half of 2005.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2864309&req=5

pone-0010355-g003: The scientific concept network for the first half of 2005.
Mentions: In order to study the evolution of different fields in physics, one must first find these fields in our network. We hypothesize that scientific fields are represented by communities in our PACS network. These communities are found using the CFinder algorithm, which is based on a clique percolation method [21]. Figs. 2 and 3 present examples of the community structure extracted utilizing CFinder.

Bottom Line: Two PACS numbers are linked if there exist publications that reference them simultaneously.The communities we identify map to known scientific fields, and their age depends on their size and activity.We expect our approach to quantifying the evolution of ideas to be relevant for making predictions about the future of science and thus help to guide its development.

View Article: PubMed Central - PubMed

Affiliation: Department of Physics and Institute for Research in Electronics and Applied Physics, University of Maryland, College Park, Maryland, United States of America.

ABSTRACT
Despite the apparent cross-disciplinary interactions among scientific fields, a formal description of their evolution is lacking. Here we describe a novel approach to study the dynamics and evolution of scientific fields using a network-based analysis. We build an idea network consisting of American Physical Society Physics and Astronomy Classification Scheme (PACS) numbers as nodes representing scientific concepts. Two PACS numbers are linked if there exist publications that reference them simultaneously. We locate scientific fields using a community finding algorithm, and describe the time evolution of these fields over the course of 1985-2006. The communities we identify map to known scientific fields, and their age depends on their size and activity. We expect our approach to quantifying the evolution of ideas to be relevant for making predictions about the future of science and thus help to guide its development.

Show MeSH
Related in: MedlinePlus