Network Effects on Scientific Collaborations

Background: The analysis of co-authorship network aims at exploring the impact of network structure on the outcome of scientific collaborations and research publications. However, little is known about what network properties are associated with authors who have increased number of joint publications and are being cited highly. Methodology/Principal Findings: Measures of social network analysis, for example network centrality and tie strength, have been utilized extensively in current co-authorship literature to explore different behavioural patterns of co-authorship networks. Using three SNA measures (i.e., degree centrality, closeness centrality and betweenness centrality), we explore scientific collaboration networks to understand factors influencing performance (i.e., citation count) and formation (tie strength between authors) of such networks. A citation count is the number of times an article is cited by other articles. We use co-authorship dataset of the research field of 'steel structure' for the year 2005 to 2009. To measure the strength of scientific collaboration between two authors, we consider the number of articles co-authored by them. In this study, we examine how citation count of a scientific publication is influenced by different centrality measures of its co-author(s) in a co-authorship network. We further analyze the impact of the network positions of authors on the strength of their scientific collaborations. We use both correlation and regression methods for data analysis leading to statistical validation. We identify that citation count of a research article is positively correlated with the degree centrality and betweenness centrality values of its co-author(s). Also, we reveal that degree centrality and betweenness centrality values of authors in a co-authorship network are positively correlated with the strength of their scientific collaborations. Conclusions/Significance: Authors' network positions in co-authorship networks influence the performance (i.e., citation count) and formation (i.e., tie strength) of scientific collaborations. © 2013 Uddin et al.published_or_final_versio

From sand to networks: a study of multi-disciplinarity

In this paper, we study empirically co-authorship networks of neighbouring scientific disciplines, and describe the system by two coupled networks. By considering a large time window, we focus on the properties of the interface between the disciplines. We also focus on the time evolution of the co-authorship network, and highlight a rich phenomenology including first order transition and cluster bouncing and merging. Finally, we present a ferro- electric-like model (CDIM), involving bond redistribution between the nodes, that reproduces qualitatively the structuring of the system in homogeneous phasesComment: submitted to europhys. let

Scientometric Analysis of Scientific Products with Co-authorship Networks: The Case of Sharif University of Technology

Identifying the most important individuals, institutions, universities, and other academic activities related to scientific production can help in collaborating and also exchanging information in various fields of science. Scientific cooperation plays an important role in promoting qualitative and quantitative scientific publications. One of the forms of collaboration is co-authorship in which two or more authors collaborate to create scientific work. Co-authorship relationships form collaboration networks that can be analyzed and visualized. The structure of networks like co-authorship can reflect the degree of internal collaboration and show the changes of information through time and other variable

Co-authorship networks in Swiss political research

Co-authorship is an important indicator of scientific collaboration. Co-authorship networks are composed of sub-communities, and researchers can gain visibility by connecting these insulated subgroups. This article presents a comprehensive co-authorship network analysis of Swiss political science. Three levels are addressed: disciplinary cohesion and structure at large, communities, and the integrative capacity of individual researchers. The results suggest that collaboration exists across geographical and language borders even though different regions focus on complementary publication strategies. The subfield of public policy and administration has the highest integrative capacity. Co-authorship is a function of several factors, most importantly being in the same subfield. At the individual level, the analysis identifies researchers who belong to the “inner circle” of Swiss political science and who link different communities. In contrast to previous research, the analysis is based on the full set of publications of all political researchers employed in Switzerland in 2013, including past publications

How are ego-centric networks of researchers coupled?

Scientific knowledge creation can be viewed as social-economic activities, which inspires us to explore researchers' interpersonal capital and its impact on scientific performance. In this study, we investigate on multiple types of interpersonal relationships between researchers, including co-authorship, author citation, and social relation, which are considered as interpersonal capital of researchers. Thus, three types of ego-centric networks (ECNs) are constructed by using the data from Twitter and Web of Science. The composition of social networks and the coupling relationships between ECNs in terms of the same researchers are analyzed. The preliminary results on the field of Cheminformatics show that most researchers tend to interact with research related accounts in social networks. The coupling degree between co-authorship networks and author citation networks is significantly higher than that between co-authorship networks and friend networks. Researchers are more likely to collaborate with the researchers who have close scholarly communication with them than the friends from social networks. This study contributes to the understanding of interpersonal relationship in scientific community. Future research will focus on the impact of interpersonal capital on scientific performance

Complete trails of co-authorship network evolution

The rise and fall of a research field is the cumulative outcome of its intrinsic scientific value and social coordination among scientists. The structure of the social component is quantifiable by the social network of researchers linked via co-authorship relations, which can be tracked through digital records. Here, we use such co-authorship data in theoretical physics and study their complete evolutionary trail since inception, with a particular emphasis on the early transient stages. We find that the co-authorship networks evolve through three common major processes in time: the nucleation of small isolated components, the formation of a tree-like giant component through cluster aggregation, and the entanglement of the network by large-scale loops. The giant component is constantly changing yet robust upon link degradations, forming the network's dynamic core. The observed patterns are successfully reproducible through a new network model