About

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I am Julie M. Birkholz a Post-doctoral researcher on the ERC funded WeChangEd Research Project at the Department of Literary StudiesGhent University, Belgium.  My research focuses on the use of the network perspective in digital literary studies. This includes building digital pipelines, to extracting networks from text, the use of Linked Data, and social network analysis. I implement a quantitative social network analysis approach to systematically compare contexts, structures and outcomes to better understand the transnational networks of women editors in Europe from 1710-1920.

Previously, I was a Post-doctoral researcher at the Centre for Higher Education Governance Ghent (CHEGG), researching networks in higher education and the social network perspective as an emerging method and paradigm in higher education research.  From 2009 – 2014 I was a PhD Candidate at the Network Institute, Vrije Universiteit Amsterdam, The Netherlands researching large social network dynamics through the lens of modern knowledge production behaviors in science. In my PhD project I investigated the dynamics of large social networks (> 1000 nodes) using a combination of social network analysis, bibliomterics and the development of computational social models – such as the mean-field model with colleagues at the VU.

My research interests also include altmetrics – http://altmetrics.org/manifesto/. My studies on this topic are related to the use and effects of social media by both higher education institutions and researchers. I have worked on questions of external validity of measuring science online, as well as how HEIs in particular are responding to the emergence of altmetrics and online dissemination practices.

Specializations: social network analysis, collaboration, higher education studies, science and technology studies, new modes of knowledge production (Mode-2, Triple Helix, new governance structures), altmetrics, & innovation.

Header image: visualization of my personal LinkedIn network, thanks to LinkedInLabs make your own network visualization for free here: http://inmaps.linkedinlabs.com/

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