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research-article

Reaching for Unique Resources: Structural Holes and Specialization in Scientific Collaboration Networks

(part four). Respondents were asked to indicate all collaborations among her and her collaborators. Collaborators on the cork board were represented with pins and collaborations were represented with rubber bands (see Figure 4). There were two follow-up questions about mutual dependencies of collaborations and about possible collaborators crucial for any tie, which were not included in the interview. Figure 4: Collecting data on collaboration networks. Interviews, lasting from 24 to 90 min, were

Michał Bojanowski, Dominika Czerniawska

Journal of Social Structure , ISSUE 1, 1–34

Article

The Structure of Collaboration Networks: An Illustration of Indian Economics

The main aim of this study is twofold: first, to examine the underlying structure of coauthorship in Indian economics; and second, to explore the link between the participation in scientific collaborations and academic visibility. We decipher the structure of co-authorship by presenting collaboration networks of scholars who published articles in six Indian economics journals during 1966-2005, which is split into four windows: 1966-75, 1976-85, 1986-95, and 1996-2005. In this study, the

M. Krishna, G.D. Bino Paul

Journal of Social Structure , ISSUE 1, –

research-article

Ukrainian and Russian organizations in Sweden and the conflict “back home”

; and others). However, this type of research is still quite scarce, while most of the diaspora studies focus mostly on the ways in which diasporas can affect the peace-building processes in their home countries, as well as the political unrest that they can be a part of in the country of settlement (Demmers, 2002; Féron, 2017). Nevertheless, all this research, among others, show that an ongoing armed conflict in the home country can have the potential to affect the collaboration networks, which

Sofiya Voytiv

Connections: The Quarterly Journal , ISSUE 1, 1–20

research-article

Academic Collaboration via Resource Contributions: An Egocentric Dataset

engaged by respondents (the egos) and their collaborators (the alters) to every collaboration. The coding was performed by two persons. Random sample of the interviews was double-checked by different researchers to ensure reliability. The data are available in table resources and described in detail below. Figure 1: Using cork board, pins, and rubber bands to collect data on collaborations. Small cards contained names or nicknames which have been masked. While collaboration networks assembled

Michał Bojanowski,, Dominika Czerniawska, Wojciech Fenrich

Connections , ISSUE 1, 1–6

research-article

Academic Collaboration via Resource Contributions: An Egocentric Dataset

engaged by respondents (the egos) and their collaborators (the alters) to every collaboration. The coding was performed by two persons. Random sample of the interviews was double-checked by different researchers to ensure reliability. The data are available in table resources and described in detail below. Figure 1: Using cork board, pins, and rubber bands to collect data on collaborations. Small cards contained names or nicknames which have been masked. While collaboration networks assembled

Michał Bojanowski,, Dominika Czerniawska, Wojciech Fenrich

Connections , ISSUE 1, 25–30

Research Article

Structural Cohesion: Visualization and Heuristics for Fast Computation

computing structural cohesion that allow a speed-up of one order of magnitude over the algorithms currently available. We analyze three large collaboration networks (co-maintenance of Debian packages, co-authorship in Nuclear Theory and High-Energy Theory) and show how our approach can help researchers measure structural cohesion in relatively large networks. We also introduce a novel graphical representation of the structural cohesion analysis to quickly spot differences across networks.

Jordi Torrents, Fabrizio Ferraro

Journal of Social Structure , ISSUE 1, 1–36

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