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Modeling the socio-semantic dynamics of scientific communities

Abstract : How are the social and semantic structures of a scientific communitydriving future research dynamics? In this thesis we combine naturallanguage processing techniques and network theory methods to analyzeavery large dataset of scientific publications in the field of computationallinguistics,i.e.the ACL Anthology. Ultimately, our goal is to understandthe role of collaborations among researchers in building and shaping thelandscape of scientific knowledge, and, symmetrically, to understand howthe configuration of this landscape influences individual trajectories ofresearchers and their interactions. We use natural language processingtools to extract the terms corresponding to scientific concepts from thetexts of the publications. Then we reconstruct a socio-semantic networkconnecting researchers and scientific concepts, and model the dynamicsof its evolution at different scales. To achieve this, we first build astatistical model, based on multivariate logistic regression, that quantifiesthe role that social and semantic features play in the evolution of thesocio-semantic network, namely in the emergence of new links. Then, wereconstruct the evolution of the field through different visualizations of theknowledge produced therein, and of the flow of researchers across thedifferent subfields of the domain. To summarize, we have shown throughour work that the combination of natural language processing techniqueswith complex network analysis makes it possible to investigate in a novelway the evolution of scientific fields.
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Contributor : Elisa Omodei <>
Submitted on : Sunday, December 21, 2014 - 12:03:47 PM
Last modification on : Monday, September 2, 2019 - 5:16:05 PM
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Elisa Omodei. Modeling the socio-semantic dynamics of scientific communities. Sociology. Ecole normale supérieure - ENS PARIS, 2014. English. ⟨NNT : 2014ENSU0005⟩. ⟨tel-01097702⟩

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