Analyzing link dynamics in scientific collaboration networks ℄ A social yield based perspective

@article{Pandey2015AnalyzingLD,
  title={Analyzing link dynamics in scientific collaboration networks ℄ A social yield based perspective},
  author={Arun Pandey and Roshni Chakraborty and Soumya Sarkar and Joydeep Chandra},
  journal={2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)},
  year={2015},
  pages={1395-1402},
  url={https://api.semanticscholar.org/CorpusID:6476032}
}
Observation indicate that certain observed behavior like presence of large number of small sized communities and highly dynamic behavior of the links in collaboration networks can be explained based on the distribution of social yield of these collaborations.
View on ACM
doi.org
3 Citations
Background Citations
1

Figures from this paper

3 Citations

Towards a Social Trust Based Measure of Scientific Productivity

The proposed measure of trust relies on a trust-based network of authors (nodes), where a link between two nodes is based on social indicators like co-authorship and citation counts, which indicates the productivity of a researcher in a given domain.

Mapping and visualization of publication networks of public university faculty in computer science and electrical engineering

The project explores collaboration networks in the computer science and electrical engineering with a focus on publication networks and an analysis of these collaborations with a focus on geospatial organization.

Link Dynamics and Community Formation in Social Networks

19 References

Behavior Evolution and Event-Driven Growth Dynamics in Social Networks

A behavior evolution-aware event-driven locality and attachedness based model to capture the growth dynamics in social networks and can better characterize the growing process and simulate important network structures observed in real networks than other non-event driven and non-behavior aware models.

Overlapping Community Structure in Co-authorship Networks: A Case Study

An extensive investigation of the overlapping community network deduced from a large-scale co-authorship network shows that they share similar topological properties, and the network of communities seems to be a good representative of the original co- authorship network.

The structure of scientific collaboration networks.

It is shown that these collaboration networks form "small worlds," in which randomly chosen pairs of scientists are typically separated by only a short path of intermediate acquaintances.

Social Dynamics of Science

This work proposes an agent-based model in which the evolution of disciplines is guided mainly by social interactions among agents representing scientists, and finds that this social model can account for a number of stylized facts about the relationships between disciplines, scholars and publications.

Community Structure and the Evolution of Interdisciplinarity in Slovenia's Scientific Collaboration Network

It is found that the flow of knowledge between different fields of research in Slovenia is in need of further stimulation, and the frequency of interdisciplinary research is only proportional with the overall growth of the network.

Coauthorship networks and patterns of scientific collaboration

This work uses data from three bibliographic databases in biology, physics, and mathematics to answer a broad variety of questions about collaboration patterns, such as the numbers of papers authors write, how many people they write them with, and what the typical distance between scientists is through the network.

Structure and Dynamics of Coauthorship, Citation, and Impact within CSCW

Methods from social network analysis and bibliometrics are used to re-examine the structures of CSCW a decade after its last systematic analysis, revealing significant but distinct patterns between papers and authors in how brokerage and closure in these networks affects impact.

The Strength of Weak Ties

Analysis of social networks is suggested as a tool for linking micro and macro levels of sociological theory. The procedure is illustrated by elaboration of the macro implications of one aspect of…

Community evolution in a scientific collaboration network

The distribution of lifespan in the network of genetic programming researchers is shown to be modeled as an exponential-law, a phenomenon yet to be explored in other empirical networks, and the parameter of minimum community size can significantly affect how communities grow over time.

Modularity and community structure in networks.

It is shown that the modularity of a network can be expressed in terms of the eigenvectors of a characteristic matrix for the network, which is called modularity matrix, and that this expression leads to a spectral algorithm for community detection that returns results of demonstrably higher quality than competing methods in shorter running times.