2. Triangulation of network metaphors The Royal Netherlands Academy of Arts and Sciences Iina Hellsten & Andrea Scharnhorst Networked Research and Digital Information – Nerdi The Royal Netherlands Academy of Arts & Sciences in Amsterdam www.nerdi.knaw.nl Andrea.scharnhorst@niwi.knaw.nl Iina.Hellsten@niwi.knaw.nl CREEN meeting, Karlsruhe June 2-4, 2005

3. Introduction: Key concepts Network: Network: a structure composed of nodes and links between the nodes Different views on network: 1) complex network theory interested in the topology and dynamics of/on networks 2) social network analysis interested in the social processes leading to network structures Related concepts: Avalanche: only in relation to evolving networks Critical events: only in relation to evolving networks

4. Network as a metaphor * Background: Metaphors robust and flexible at the same time; network as a metaphor of specific structure as well as the relations within that structure * Focus: Triangulation of the different meanings and uses of the metaphor of network * Aim: Colliding the analysis of the topology of networks and the semantics in the networks * Question: Can a meta-perspective of the notions of network help us combine the analysis of the topology of network and the communication in the network?

5. Social network theory Complex network theory Social mechanisms behind the network structure Dynamic mechanisms behind the network structure

6. Network: Complex network theory FOCUS: large networks; universalities in the topology of networks & dynamics of the evolution of the networks DISCIPLINARY BACKGROUND: statistical physics,non-linear dynamics; self-organization theories, complexity theory UNDERLYING VIEW ON COMMUNICATION as transfer of information DEFINITION OF NETWORK: “Networks with complex topology describe systems as diverse as the cell or the World Wide Web. The emergence of these networks is driven by self-organizing processes that are governed by simple but generic laws.”(Barabási et al., 2001)

7. Network: Social network analysis DEFINITION: “Social network analysis focuses on relationships among social entities, and on the patterns and implications of these relationships” (Wasserman & Faust, 1994) FOCUS: small networks; social relations between individuals; communication in the networks UNDERLYING VIEW ON COMMUNICATION as cultural sharing of ideas and forming groups DISCIPLINARY BACKGROUND: social sciences, sociology

8. “Networks” and “complex networks”, Web of Science, 1981-2004.

9. “Complex networks” in different disciplines, 1990-2002.

11. Cluster 1: ACTIVE, BIOLOGICAL, FUNCTION, COMMUNICATION Cluster 2: FUNCTIONAL, ORGANIZATION, INFORMATION, WATER Cluster 3: CELL, CELLS, PROTEIN, MOLECULAR, MOLECULES / NEURON SYNAPTIC Cluster 4: BRAIN, CYTOKINES, EXPRESSION, RESPONSE, GENE / PATHWAYS, SIGNALING Cluster 5: ALGORITHM, RELIABILITY, COMPUTER Cluster 6: CONTROL MANAGEMENT / FLOW, PERFORMANCE, ROUTING, TRAFFIC Cluster 7: CONNECTIONS, CONNECTIVITY, FREE, RANDOM, GRAPHS, SOCIAL, STRUCTURAL Cluster 8: DYNAMICS, POWER, SMALL, STRUCTURE, SIMULATION, SCALE, WEB, WORLD / EVOLUTION, INTERACTIONS, GROWTH, GENETIC

13. Trading zone topic bursts Social networksComplex networks communities Semantic maps Hyperlinks Knowledge domains avalanches clusters Topology & semantics Ego network Co-authorship network Dynamic mechanisms of growth & decay Time series (snapshots) of one network

14. Further questions * Would it be possible to analyze large evolving networks from the point of view of communication as sharing of ideas instead of transfer of information? * How to apply the different notions of network in the analysis of the case studies? * Using concept pairs from social network & complex network theory (topic bursts – avalanches; social communities – clusters)? *