Exploratory social network analysis with Pajek
By Bethany S. Dohleman. 2006
1,368 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/4c215523f9a874f5e4f58a8557b001ab8728b5e0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Nathalie Henry Riche
- Jean-Daniel Fekete
- Javier A. Reyes
- Stefano Schiavo
- Michael J. McGuffin
- Giorgio Fagiolo
- M. Shafique
- Ben Shneiderman
Citations in the corpus
- The evolution of the world trade web: a weighted-network analysis (2010, background): “5( w ij + w ji )), see De Nooy et al. (2005). nearly identified with OECD members.”
- A review of theory and practice in scientometrics (2015, methodology): “New algorithms and mapping techniques such as the Blondel algorithm (Blondel et al., 2008) and the Pajek mapping software have greatly enhanced the visualization of high-dimensional datasets (de Nooy et al., 2011).”
- Network Pharmacology Databases for Traditional Chinese Medicine: Review and Assessment (2019, methodology): “Pajek (Dohleman, 2006) is another powerful network analysis tool that is used to examine various complex non-linear networks.”
- The processing of verb-argument constructions is sensitive to form, function, frequency, contingency and prototypicality (2014, methodology): “We apply networks science, graph-based algorithms (de Nooy et al. 2010) to build semantic networks in which the nodes represent verb types and the edges strong semantic similarity for each VAC.”
- Don't follow me: Spam detection in Twitter (2010, methodology): “20 random users and their followers and friends are collected from Twitter’s public timeline and the figure is drawn using Pajek software (Nooy et al., 2004).”
- Social network analysis: developments, advances, and prospects (2010, methodology): “More recently, PAJEK has been developed by Vladimir Batagelj at the University of Ljubljana as a way of handling large-scale data sets and, in particular, using visual methods of representation (see De Nooy et al. 2005).”
- Network Pharmacology: A New Approach for Chinese Herbal Medicine Research (2013, methodology): “At present, most visualization of network pharmacology is through professional tools such as Cytoscape [37], GUESS [38], and Pajek [39].”