• Corpus ID: 211217126

Degree, Closeness, and Betweenness: Application of group centrality measurements to explore macro-disciplinary evolution diachronically

@inproceedings{Ni2013DegreeCA,
  title={Degree, Closeness, and Betweenness: Application of group centrality measurements to explore macro-disciplinary evolution diachronically},
  author={Chaoqun Ni and Cassidy R. Sugimoto and Jiepu Jiang},
  year={2013}
}
jij29@pitt.edu University of Pittsburgh, School of Information Sciences, 135 N. Bellefield Ave., Pittsburgh, PA 15260 (United States) Abstract Three group centrality measures--degree, closeness, and betweenness--are utilized in this paper to explore the role of disciplines in two journal co-citation networks by using 677 journals from 40 disciplines categorized by Web of Knowledge. The result shows that social science disciplines play a more central role in knowledge communication and… 

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References

SHOWING 1-10 OF 23 REFERENCES

Mapping library and information science in China: a coauthorship network analysis

This paper constructs the LIS coauthorship network using data from 18 core source LIS journals in China covering 6 years, and identifies some key features of this network: this network is a small-world network, and follows the scale-free character.

Maps of science as interdisciplinary discourse: co-citation contexts and the role of analogy

This analysis reveals that interdisciplinary connections are often based on authors’ perceptions of analogous problems across scientific domains, and cue words drawn from the citation contexts suggest that these connections are viewed as important and ripe with both opportunity and risk.

Mapping the backbone of science

A new map representing the structure of all of science, based on journal articles, is presented, including both the natural and social sciences, including biochemistry, which appears as the most interdisciplinary discipline in science.

Centrality in social networks conceptual clarification

Detecting, identifying and visualizing research groups in co-authorship networks

A method for detecting, identifying and visualizing research groups and the structures of the socio-centric and co-authorship networks and the strategies underlying collaboration among researchers, were discussed with the members of the departments analyzed.

A global map of science based on the ISI subject categories

The nested maps of science (corresponding to 14 factors, 172 categories, and 6,164 journals) are brought online and an analysis of interdisciplinary relations is pursued at three levels of aggregation using the newly added ISI subject category of "Nanoscience & nanotechnology".

Using field cocitation analysis to assess reciprocal and shared impact of LIS/MIS fields

Using Field Co-citation Analysis to Assess Reciprocal and Shared Impact of LIS/MIS Fields Fields is used to assess reciprocity and shared impact in information systems research.

Social Network Analysis: Methods and Applications

This paper presents mathematical representation of social networks in the social and behavioral sciences through the lens of dyadic and triadic interaction models, which provide insights into the structure and dynamics of relationships between actors and groups.

Centrality and network flow

Journal maps on the basis of Scopus data: A comparison with the Journal Citation Reports of the ISI

Using the Scopus dataset (1996–2007) a grand matrix of aggregated journal-journal citations was constructed. This matrix can be compared in terms of the network structures with the matrix contained