Exploration of an Interdisciplinary Scientific Landscape
arXiv:1712.00805 · doi:10.1007/s11192-019-03090-3
Abstract
Patterns of interdisciplinarity in science can be quantified through diverse complementary dimensions. This paper studies as a case study the scientific environment of a generalist journal in Geography, Cybergeo, in order to introduce a novel methodology combining citation network analysis and semantic analysis. We collect a large corpus of around 200,000 articles with their abstracts and the corresponding citation network that provides a first citation classification. Relevant keywords are extracted for each article through text-mining, allowing us to construct a semantic classification. We study the qualitative patterns of relations between endogenous disciplines within each classification, and finally show the complementarity of classifications and of their associated interdisciplinarity measures. The tools we develop accordingly are open and reusable for similar large scale studies of scientific environments.
24 pages, 11 figures, 1 table. Published in Scientometrics
References in corpus (6)
- Fast unfolding of communities in large networks
- Modularity and community structure in networks
- Interdisciplinarity: A Nobel Opportunity
- The Stochastic Topic Block Model for the Clustering of Vertices in Networks with Textual Edges
- Classifying Patents Based on their Semantic Content
- An Applied Knowledge Framework to Study Complex Systems