TY - JOUR AU - Cerinšek, Monika AU - Batagelj, Vladimir T1 - Network analysis of Zentralblatt MATH data JO - Scientometrics PY - 2015/ VL - 102 IS - 1 SP - 977 EP - 1001 UR - http://dx.doi.org/10.1007/s11192-014-1419-z M3 - 10.1007/s11192-014-1419-z KW - scientometrics KW - zentralblatt KW - bibliometrics KW - coauthor KW - analysis KW - citation KW - math L1 - SN - N1 - Network analysis of Zentralblatt MATH data - Springer N1 - AB - We analyze the data about works (papers, books) from the time period 1990–2010 that are collected in Zentralblatt MATH database. The data were converted into four 2-mode networks (works ER - TY - JOUR AU - Batagelj, Vladimir AU - Zaveršnik, Matjaž T1 - Fast algorithms for determining (generalized) core groups in social networks JO - Advances in Data Analysis and Classification PY - 2011/ VL - 5 IS - 2 SP - 129 EP - 145 UR - http://dx.doi.org/10.1007/s11634-010-0079-y M3 - 10.1007/s11634-010-0079-y KW - social KW - analysis KW - core KW - network KW - sna L1 - SN - N1 - N1 - AB - The structure of a large network (graph) can often be revealed by partitioning it into smaller and possibly more dense sub-networks that are easier to handle. One of such decompositions is based on “ ER - TY - JOUR AU - Batagelj, Vladimir AU - Zaveršnik, Matjaž T1 - Fast algorithms for determining (generalized) core groups in social networks JO - Advances in Data Analysis and Classification PY - 2011/ VL - 5 IS - 2 SP - 129 EP - 145 UR - http://dx.doi.org/10.1007/s11634-010-0079-y M3 - 10.1007/s11634-010-0079-y KW - graph KW - core L1 - SN - N1 - Advances in Data Analysis and Classification, Volume 5, Number 2 - SpringerLink N1 - AB - The structure of a large network (graph) can often be revealed by partitioning it into smaller and possibly more dense sub-networks that are easier to handle. One of such decompositions is based on “ k -cores”, proposed in 1983 by Seidman. Together with connectivity components, cores are one among few concepts that provide efficient decompositions of large graphs and networks. In this paper we propose an efficient algorithm for determining the cores decomposition of a given network with complexity $$O(m)$$, where m is the number of lines (edges or arcs). In the second part of the paper the classical concept of k -core is generalized in a way that uses a vertex property function instead of degree of a vertex. For local monotone vertex property functions the corresponding generalized cores can be determined in $$O(motn))$$ time, where n is the number of vertices and Δ is the maximum degree. Finally the proposed algorithms are illustrated by the analysis of a collaboration network in the field of computational geometry. ER - TY - JOUR AU - BATAGELJ, VLADIMIR T1 - Social Network Analysis, Large-scale JO - Encyclopedia of Complexity and System Science PY - 2009/ VL - IS - SP - EP - UR - http://vlado.fmf.uni-lj.si/pub/networks/doc/mix/LargeSNA.pdf M3 - KW - social KW - analysis KW - network KW - sna KW - batagelj L1 - SN - N1 - N1 - AB - ER - TY - CONF AU - Ahmed, Adel AU - Batagelj, Vladimir AU - Fu, Xiaoyan AU - Hong, Seok-Hee AU - Merrick, Damian AU - Mrvar, Andrej A2 - T1 - Visualisation and analysis of the internet movie database T2 - Visualization, 2007. APVIS '07. 2007 6th International Asia-Pacific Symposium on PB - CY - PY - 2007/feb. M2 - VL - IS - SP - 17 EP - 24 UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4126213&tag=1 M3 - 10.1109/APVIS.2007.329304 KW - analysis KW - core KW - imdb L1 - SN - N1 - IEEE Xplore - Visualisation and analysis of the internet movie database N1 - AB - In this paper, we present a case study for the visualisation and analysis of large and complex temporal multivariate networks derived from the Internet movie database (IMDB). Our approach is to integrate network analysis methods with visualisation in order to address scalability and complexity issues. In particular, we defined new analysis methods such as (p,q)-core and 4-ring to identify important dense subgraphs and short cycles from the huge bipartite graphs. We applied island analysis for a specific time slice in order to identify important and meaningful subgraphs. Further, a temporal Kevin Bacon graph and a temporal two mode network are extracted in order to provide insight and knowledge on the evolution. ER - TY - BOOK AU - de Nooy, Wouter AU - Mrvar, Andrej AU - Batagelj, Vladimir A2 - T1 - Exploratory Social Network Analysis with Pajek PB - Cambridge University Press AD - New York, NY, USA PY - 2005/ VL - IS - 27 SP - EP - UR - http://www.amazon.com/Exploratory-Network-Analysis-Structural-Sciences/dp/0521602629%3FSubscriptionId%3D192BW6DQ43CK9FN0ZGG2%26tag%3Dws%26linkCode%3Dxm2%26camp%3D2025%26creative%3D165953%26creativeASIN%3D0521602629 M3 - KW - graph KW - visualisation KW - social KW - pajek KW - analysis KW - tool KW - network KW - sna L1 - SN - 0521602629 N1 - Amazon.com: Exploratory Social Network Analysis with Pajek (Structural Analysis in the Social Sciences) (9780521602624): Wouter de Nooy, Andrej Mrvar, Vladimir Batagelj: Books N1 - AB - ER - TY - BOOK AU - de Nooy, Wouter AU - Mrvar, Andrej AU - Batagelj, Vladimir A2 - T1 - Exploratory Social Network Analysis with Pajek (Structural Analysis in the Social Sciences) PB - Cambridge University Press AD - PY - 2005/ VL - IS - SP - EP - UR - http://www.amazon.com/Exploratory-Network-Analysis-Structural-Sciences/dp/0521602629 M3 - KW - book KW - exploratory KW - social KW - pajek KW - analysis KW - network KW - structure KW - sna L1 - SN - 0521602629 N1 - Amazon.com: Exploratory Social Network Analysis with Pajek (Structural Analysis in the Social Sciences) (9780521602624): Wouter de Nooy, Andrej Mrvar, Vladimir Batagelj: Books N1 - AB - ER - TY - JOUR AU - Batagelj, Vladimir AU - Zaversnik, Matjaz T1 - Generalized Cores JO - CoRR PY - 2002/ VL - cs.DS/0202039 IS - SP - EP - UR - http://dblp.uni-trier.de/db/journals/corr/corr0202.html#cs-DS-0202039 M3 - KW - core KW - p-core KW - generalized L1 - SN - N1 - N1 - AB - ER - TY - GEN AU - Batagelj, Vladimir AU - Zaveršnik, Matjaž A2 - T1 - Generalized Cores JO - PB - AD - PY - 2002/ VL - IS - SP - EP - UR - http://arxiv.org/abs/cs/0202039 M3 - KW - core KW - p-core KW - generalized L1 - N1 - [cs/0202039] Generalized Cores N1 - AB - Cores are, besides connectivity components, one among few concepts that

provides us with efficient decompositions of large graphs and networks.

In the paper a generalization of the notion of core of a graph based on

vertex property function is presented. It is shown that for the local monotone

vertex property functions the corresponding cores can be determined in $O(m

max ( log n))$ time. ER - TY - CHAP AU - Batagelj, Vladimir AU - Mrvar, Andrej AU - Zaveršnik, Matjaž A2 - Kratochvíyl, Jan T1 - Partitioning Approach to Visualization of Large Graphs T2 - Graph Drawing PB - Springer CY - Berlin / Heidelberg PY - 1999/ VL - 1731 IS - SP - 90 EP - 97 UR - http://dx.doi.org/10.1007/3-540-46648-7_9 M3 - 10.1007/3-540-46648-7_9 KW - graph KW - core L1 - SN - 978-3-540-66904-3 N1 - Abstract - SpringerLink N1 - AB - The structure of large graphs can be revealed by partitioning graphs to smaller parts, which are easier to handle. In the paper we propose the use of core decomposition as an efficient approach for partitioning large graphs. On the selected subgraphs, computationally more intensive, clustering and blockmodeling can be used to analyze their internal structure. The approach is illustrated by an analysis of Snyder & Kick’s world trade graph. ER -