Streams of Thought: Knowledge Flows and Intellectual Cohesion in a Multidisciplinary Era

Rawlings, Craig M.; McFarland, Daniel A.; Dahlander, Linus; Wang, Dan

doi:10.1093/sf/sov004

Cited by 33 publications

(26 citation statements)

References 46 publications

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“…A common concern is the possibility that dyads bias standard errors downward, and because this bias can come from multiple sources of repeated observations, standard fixedand randomeffects models provide insufficient solutions. We therefore follow the strategy of using multiway clustering in order to estimate standard errors, using the estimation procedures outlined in Cameron, Gelbach, and Miller (2011), an approach that is being employed in a growing number of network analytic studies of dyads (Dahlander and McFarland 2013;Kleinbaum, Stuart, and Tushman 2013;Rawlings et al 2015). For hypothesis 2, we estimate a logistic regression predicting the probability of an i to j tension PrðT ij 5 1Þ:…”

Section: Methodsmentioning

confidence: 99%

The Structural Balance Theory of Sentiment Networks: Elaboration and Test

Rawlings¹,

Friedkin

2017

American Journal of Sociology

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Structural balance theory attends to a group's network of sentiments and posits that this network alters over time toward particular structural forms. Current work on the theory is focused on understanding the mechanisms that alter sentiments as a function of the configuration of sentiments in which they are embedded. Although the theory assumes tension reduction mechanisms, there has been no effort to directly measure and model the temporal changes of individuals' relational tensions that are predicted by the theory. This article elaborates and tests balance theory with an empirical analysis of its posited interpersonal tensions and their reductions via a sentiment conversion process. In addition, the authors open a new line of inquiry on the theory's scope conditions and point to a community commitment condition that is involved in the realization of structural balance. Their analysis draws on a unique suite of multiwave measures obtained from the Urban Communes Data Set. Georg Simmel posed an interesting, seemingly simple, question: what are the implications of enlarging a dyadic relationship to a triad of individuals? His insight, which might be stated as "social structure matters," was that the

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Section: Methodsmentioning

confidence: 99%

The Structural Balance Theory of Sentiment Networks: Elaboration and Test

Rawlings¹,

Friedkin

2017

American Journal of Sociology

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“…Universities and research centers have actively promoted collaboration among faculty. Policy pushes at the federal level have also been supportive of this trend (Bikard et al 2015, Clark & Llorens 2012, Cummings & Kiesler 2007, Rawlings et al 2015: Examples include the Roadmap initiative of the National Institutes of Health (NIH) and the related workshop, titled "Catalyzing Team Science" (Kennedy 2003). Communication technology has been instrumental (Araujo et al 2014, Binz-Scharf et al 2015, and travel is cheaper (Katz & Martin 1997).…”

Section: What Drives Collaboration?mentioning

confidence: 99%

From Sole Investigator to Team Scientist: Trends in the Practice and Study of Research Collaboration

2016

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This article reviews trends in the practice and study of research collaboration, focusing on journal publications in academic science. I briefly describe the different styles and types of collaboration and then focus on the drivers of the trend toward increased collaboration and on its consequences for both individual researchers and science more generally. Scholarship on collaboration seems partial to delineating its benefits; this review highlights the increasing body of research that focuses instead on the possible costs of collaboration. The synthesis reveals several topics that are ripe for investigation, including the impact of collaboration on the contributing authors and their work, the use of multiple methods and measures, and research integrity. I applaud a few recent efforts to overcome the perennial file-drawer problem by gaining access to collaborations that do not result in publication and thus are typically removed from public review and the research analyst's eye.

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“…While Post-Docs try to improve their reputation, demonstrate that they can work with others and on different subjects, collaboration among professors might be differently motivated. Professors build on 'ties that last' (Rawlings et al, 2015) with regard to former collaboration projects, counting on their existing reputation and multifold connections within the research community.…”

Section: Gender Institutional Affiliation and Status In Academic Colmentioning

confidence: 99%

“…To investigate both co-authorship and acknowledgement relations, and, at the same time, account for disciplinary differences (Leahey, 2006;Leahey & Moody, 2014;Rawlings, McFarland, Dahlander, & Wang, 2015), three sub-disciplinary political science journals from Germany are selected, the Moreover, comparative politics, international relations and political theory seem to be on opposite sides of collaboration patterns in political science. While comparative politics scholars show a stronger pattern of collaboration, political theorists seem to publish predominantly single authored articles; international relations scholars are in between this spectrum (Leifeld & Ingold, 2016;Metz & Jäckle, 2017).…”

Section: Introductionmentioning

confidence: 99%

Kudos to you! Comparing co-authorships and acknowledgements in political science journals from Germany

Wallaschek¹,

Heiberger²

2019

Preprint

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Scientific research on academic collaboration focuses on co-authorships, citations and acknowledgements as 'reward triangle'. However, acknowledgements have received comparatively little attention. In this paper, we compare co-authorship and acknowledgement networks and investigate conditions that influence their formation (gender, institutional affiliation and status of authors and acknowledged individuals). We select three sub-disciplinary political science journals from Germany between 2010 and 2017. We employ techniques from social network analysis to compare these conditions by using homophily measures. The results demonstrate that co-authorships have a rather sparse network while including acknowledgements reveals hidden collaboration structures. Moreover, scholars from the same institution are more likely to co-author and acknowledge each other while we show heterophily effects for acknowledging and co-authoring behavior of professors. We also identify an underrepresentation of female academics as authors and credit-givers alike. Thus, our exploratory study reveals similarities and differences patterns for co-authorships and acknowledgements providing new ground for future studies on all aspects of collaborative behavior in science.

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Streams of Thought: Knowledge Flows and Intellectual Cohesion in a Multidisciplinary Era

Cited by 33 publications

References 46 publications

The Structural Balance Theory of Sentiment Networks: Elaboration and Test

The Structural Balance Theory of Sentiment Networks: Elaboration and Test

From Sole Investigator to Team Scientist: Trends in the Practice and Study of Research Collaboration

Kudos to you! Comparing co-authorships and acknowledgements in political science journals from Germany

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