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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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Relation between fields density and their age.A. Variation of the mean density depending on the branch age, for different values of threshold . B. Dependence of the mean density on the fields’ position in the phylomemy. Fields in the phylomemy have a much higher density than ephemeral fields, and their density distribution suggests trends in the “life cycle” of thematic fields: the density grows when a new field is emerging, and decreases when the field starts to be neglected by the community. Error bars represent the 95% confidence interval. Only lower bars are plotted for better visibility.
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pone-0054847-g005: Relation between fields density and their age.A. Variation of the mean density depending on the branch age, for different values of threshold . B. Dependence of the mean density on the fields’ position in the phylomemy. Fields in the phylomemy have a much higher density than ephemeral fields, and their density distribution suggests trends in the “life cycle” of thematic fields: the density grows when a new field is emerging, and decreases when the field starts to be neglected by the community. Error bars represent the 95% confidence interval. Only lower bars are plotted for better visibility.

Mentions: We first plotted the average density of the fields against their branch age (see Fig. 5-a). For a large range of values of , the density is positively correlated with the age of the current field: long lasting fields tend to feature a density far higher than the average value.


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

Chavalarias D, Cointet JP - PLoS ONE (2013)

Relation between fields density and their age.A. Variation of the mean density depending on the branch age, for different values of threshold . B. Dependence of the mean density on the fields’ position in the phylomemy. Fields in the phylomemy have a much higher density than ephemeral fields, and their density distribution suggests trends in the “life cycle” of thematic fields: the density grows when a new field is emerging, and decreases when the field starts to be neglected by the community. Error bars represent the 95% confidence interval. Only lower bars are plotted for better visibility.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0054847-g005: Relation between fields density and their age.A. Variation of the mean density depending on the branch age, for different values of threshold . B. Dependence of the mean density on the fields’ position in the phylomemy. Fields in the phylomemy have a much higher density than ephemeral fields, and their density distribution suggests trends in the “life cycle” of thematic fields: the density grows when a new field is emerging, and decreases when the field starts to be neglected by the community. Error bars represent the 95% confidence interval. Only lower bars are plotted for better visibility.
Mentions: We first plotted the average density of the fields against their branch age (see Fig. 5-a). For a large range of values of , the density is positively correlated with the age of the current field: long lasting fields tend to feature a density far higher than the average value.

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