Visualization of Networked Collaboration in DigitalEcosystems through Two-mode Network Patterns International Conference o...
Overview1. Motivation and conceptual approach      Application of two-mode networks for analyzing collaboration in Digital...
1. Motivation and research design Learners and knowledge workers are  part of a Digital Ecosystem Complex interaction fl...
2. Related work: Visualization techniques & network modesVisualization techniques    linear structures, hierarchies, netw...
2. Related work: Pattern mining in networked structuresNetwork pattern: defined according to relations between nodes as we...
3. Comparison of visualizations: Methodology Development of own algorithms to pre-process data, generate two-  mode netwo...
3. Comparison of visualizations: One vs. Two-mode NetworksOne-mode networks:+ better overview+ only one type of nodes (eas...
3. Comparison of visualizations: Pattern detection Roles identifiably in one and two-mode networks! Yet, two-mode networ...
3. Comparison of visualizations: Homogeneity of networks Collaboration can be characterized in terms of the homogeneity o...
4. Conclusions and future workDiscussion of our pattern approach for two-mode networks: More detailed analysis and semant...
Thanks for your attention!     The research leading to these results has received funding from the European     Communitys...
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Visualizing Networked Collaboration

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MEDES’11, November 21-24, 2011, San Francisco, USA.

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Visualizing Networked Collaboration

  1. 1. Visualization of Networked Collaboration in DigitalEcosystems through Two-mode Network Patterns International Conference on Management of Emergent DigitalEcoSystems (MEDES’11), San Francisco, November 21-23, 2011 Felix Mödritscher, Wolfgang Taferner Vienna University of Economics and Business, Austria Ahmet Soylu, Patrick De Causmaecker Department of Computer Science, K.U. Leuven, Belgium © role-project.eu
  2. 2. Overview1. Motivation and conceptual approach Application of two-mode networks for analyzing collaboration in Digital Ecosystems2. Related work Visualization techniques, network modes, & pattern mining in networked structures3. Comparison of different network visualizations Methodology, network modes, pattern detection, & homogeneity considerations4. Conclusions & future work Pros and cons of this research; next steps21-23/11/2011 MEDES’11, San Francisco, 2011 2/11 , © role-project.eu
  3. 3. 1. Motivation and research design Learners and knowledge workers are part of a Digital Ecosystem Complex interaction flows with other actors, tools, artifacts, & communities Many analysis methods based on one-mode networks (like SNA), thus reducing complexity but also informationResearch design: Idea: Application of two-mode networks to analyze and visualize networked collaboration in Digital Ecosystems (a) review of related work, (b) comparing one and two-mode networks21-23/11/2011 MEDES’11, San Francisco, 2011 3/11 , © role-project.eu
  4. 4. 2. Related work: Visualization techniques & network modesVisualization techniques linear structures, hierarchies, networks, multi-dim. spaces, maps [Andrews 2002] exploration environments for discovering relationships, data & document mining, analyzing mass data-sets, creating visual awareness etc. [Fayyad et al. 2002] Web 2.0: harnessing the collective intelligence of Digital Ecosystems (Facebook, Google, Bing, Apple Stores, Mendeley, Flickr etc.)Network modes network visualization can “help users to understand and manage the complexity of large, structured hypermedia collections” [Andrews 1998] however, one-mode networks in most cases (SNA, tag networks, citation networks etc.) two-mode networks: bipartite graphs e.g. ‘Deep South’ project [Davis et al. 1941]21-23/11/2011 MEDES’11, San Francisco, 2011 4/11 , © role-project.eu
  5. 5. 2. Related work: Pattern mining in networked structuresNetwork pattern: defined according to relations between nodes as well as thresholds for metrics on nodes and edges (rules)PALADIN [Klamma et al. 2006]: patterns in social networks (roles like conversionalists or trolls)  restricted to one-mode networksgSpan [Yan & Han 2002]: performant technique for graph-based substructure pattern mining  not applicable for bipartite graphsBlockmodeling approach [Dorejan et al. 2004]: identifying patterns in k-partite graphs  very costly processing (not performant)21-23/11/2011 MEDES’11, San Francisco, 2011 5/11 , © role-project.eu
  6. 6. 3. Comparison of visualizations: Methodology Development of own algorithms to pre-process data, generate two- mode networks and visualize collaboration in Digital Ecosystems Focus on MediaWiki instances  Wiki of the SONIVIS project (19 contributors, 342 articles, 600 relations)  German version of Wikiversity (1.695 contributors, 9.751 articles, 21.288 relations)  German version of Wikiquote (25.911 contributors, 9.120 articles, 136.383 relations) Raw data from MySQL database, transformed according to a specific data model (used by the SONIVIS software) Imported into the R framework, an open source software for statistical computing and graphics Creation of two-mode networks and visualizations with R21-23/11/2011 MEDES’11, San Francisco, 2011 6/11 , © role-project.eu
  7. 7. 3. Comparison of visualizations: One vs. Two-mode NetworksOne-mode networks:+ better overview+ only one type of nodes (easier to understand)- loss of information (women connected by which event(s)?)Two-mode networks:+ can be more complex and realistic for a real-world problem+ possibility of more detailed analysis- might be too much details (information overload)Conclusion: combined application of both network types (overview, details on demand)21-23/11/2011 MEDES’11, San Francisco, 2011 7/11 , © role-project.eu
  8. 8. 3. Comparison of visualizations: Pattern detection Roles identifiably in one and two-mode networks! Yet, two-mode networks allow defining rules in a more fine-grained way (on bipartite graphs) Pioneers within the Wikiversity platform (Pioneer = at least 0.1% of all articles AND 40% to 80% ratio of single to multi-authored articles) Furthermore, two-mode networks enable zooming into large networks through neighbourhood visualizations of patterns: SONIVIS vs. Wikiversity21-23/11/2011 MEDES’11, San Francisco, 2011 8/11 , © role-project.eu
  9. 9. 3. Comparison of visualizations: Homogeneity of networks Collaboration can be characterized in terms of the homogeneity of a networks  Wikiversity vs. Wikiquote Wikiversity: slightly connected sub-networks with 11 ‘Pioneers’, 4 ‘Networkers’ (connected to a wide range of users) and 1 ‘Community Star’ (well connected through their contributions) Wikiquote: relations between articles and contributes homogeneously distributed; 0 ‘Pioneers’, 19 ‘Networkers’ and 25 ‘Community Stars’21-23/11/2011 MEDES’11, San Francisco, 2011 9/11 , © role-project.eu
  10. 10. 4. Conclusions and future workDiscussion of our pattern approach for two-mode networks: More detailed analysis and semantics for real-world problems (no loss of information) Possibility to define, identify and visualize patterns of collaboration in Digital Ecosystems (like Wikis) Possibility to zoom into large networks (avoiding information overload) Depending on scenario, one-mode network visualization might be better (to reduce complexity or the network size)Future work: Application of the pattern-based analysis and visualization approach to other domains (like personal learning environments) Further exploration studies with other Wikis21-23/11/2011 MEDES’11, San Francisco, 2011 10/11 , © role-project.eu
  11. 11. Thanks for your attention! The research leading to these results has received funding from the European Communitys Seventh Framework Programme (FP7/ 2007-2013) under grant agreement no 231396 (ROLE project).21-23/11/2011 MEDES’11, San Francisco, 2011 11/11, © role-project.eu

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