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Phylomemetic patterns in science evolution--the rise and fall of scientific fields.

Chavalarias D, Cointet JP - PLoS ONE (2013)

Bottom Line: We introduce an automated method for the bottom-up reconstruction of the cognitive evolution of science, based on big-data issued from digital libraries, and modeled as lineage relationships between scientific fields.We refer to these dynamic structures as phylomemetic networks or phylomemies, by analogy with biological evolution; and we show that they exhibit strong regularities, with clearly identifiable phylomemetic patterns.Within the framework of a quantitative epistemology, this approach raises the question of predictibility for science evolution, and sketches a prototypical life cycle of the scientific fields: an increase of their cohesion after their emergence, the renewal of their conceptual background through branching or merging events, before decaying when their density is getting too low.

View Article: PubMed Central - PubMed

Affiliation: Complex Systems Institute of Paris Ile-de-France, Paris, France. david.chavalarias@ehess.fr

ABSTRACT
We introduce an automated method for the bottom-up reconstruction of the cognitive evolution of science, based on big-data issued from digital libraries, and modeled as lineage relationships between scientific fields. We refer to these dynamic structures as phylomemetic networks or phylomemies, by analogy with biological evolution; and we show that they exhibit strong regularities, with clearly identifiable phylomemetic patterns. Some structural properties of the scientific fields - in particular their density -, which are defined independently of the phylomemy reconstruction, are clearly correlated with their status and their fate in the phylomemy (like their age or their short term survival). Within the framework of a quantitative epistemology, this approach raises the question of predictibility for science evolution, and sketches a prototypical life cycle of the scientific fields: an increase of their cohesion after their emergence, the renewal of their conceptual background through branching or merging events, before decaying when their density is getting too low.

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Inter-temporal fields matching.
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pone-0054847-g002: Inter-temporal fields matching.

Mentions: To achieve suitable inter-temporal matching between fields, for each field built over the period we need to find the field or union of fields from which it has inherited (cf.fig. 2). We assume that the time scale of the transformation of scientific fields is sufficiently slow to allow our empirical observation device to track “infinitesimal” transformations - meaning that the characteristic time scale over which we observe those transformations (typically year) is greater than the fields’ actual pace of transformation (note that this principle of continuity had already been proposed a long time ago by Simmel [25] to track the “persistence” of social groups). We are thus trying to identify the past field or the combination of past fields at period (since we allow for merging events) that would explain the compositions in the most economic way - that is to say, the link between and its parent(s) involving the smallest number of changes (terms which are added or removed).


Phylomemetic patterns in science evolution--the rise and fall of scientific fields.

Chavalarias D, Cointet JP - PLoS ONE (2013)

Inter-temporal fields matching.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3569444&req=5

pone-0054847-g002: Inter-temporal fields matching.
Mentions: To achieve suitable inter-temporal matching between fields, for each field built over the period we need to find the field or union of fields from which it has inherited (cf.fig. 2). We assume that the time scale of the transformation of scientific fields is sufficiently slow to allow our empirical observation device to track “infinitesimal” transformations - meaning that the characteristic time scale over which we observe those transformations (typically year) is greater than the fields’ actual pace of transformation (note that this principle of continuity had already been proposed a long time ago by Simmel [25] to track the “persistence” of social groups). We are thus trying to identify the past field or the combination of past fields at period (since we allow for merging events) that would explain the compositions in the most economic way - that is to say, the link between and its parent(s) involving the smallest number of changes (terms which are added or removed).

Bottom Line: We introduce an automated method for the bottom-up reconstruction of the cognitive evolution of science, based on big-data issued from digital libraries, and modeled as lineage relationships between scientific fields.We refer to these dynamic structures as phylomemetic networks or phylomemies, by analogy with biological evolution; and we show that they exhibit strong regularities, with clearly identifiable phylomemetic patterns.Within the framework of a quantitative epistemology, this approach raises the question of predictibility for science evolution, and sketches a prototypical life cycle of the scientific fields: an increase of their cohesion after their emergence, the renewal of their conceptual background through branching or merging events, before decaying when their density is getting too low.

View Article: PubMed Central - PubMed

Affiliation: Complex Systems Institute of Paris Ile-de-France, Paris, France. david.chavalarias@ehess.fr

ABSTRACT
We introduce an automated method for the bottom-up reconstruction of the cognitive evolution of science, based on big-data issued from digital libraries, and modeled as lineage relationships between scientific fields. We refer to these dynamic structures as phylomemetic networks or phylomemies, by analogy with biological evolution; and we show that they exhibit strong regularities, with clearly identifiable phylomemetic patterns. Some structural properties of the scientific fields - in particular their density -, which are defined independently of the phylomemy reconstruction, are clearly correlated with their status and their fate in the phylomemy (like their age or their short term survival). Within the framework of a quantitative epistemology, this approach raises the question of predictibility for science evolution, and sketches a prototypical life cycle of the scientific fields: an increase of their cohesion after their emergence, the renewal of their conceptual background through branching or merging events, before decaying when their density is getting too low.

Show MeSH
Related in: MedlinePlus