Triangulation of “network” metaphors

1. Triangulation of “network” metaphors Andrea Scharnhorst, Iina Hellsten The Virtual Knowledge Studio, Amsterdam Paper given at the EXYSTENCE topical workshop Innovation networks – new approaches in modeling and analyzing, Augsburg October 2005. Do not cite without prior permission of the author/s.

2. The Network hype “COMPLEX NETWORK,S” Web of science

3. The context of networks

4. What is a network for …. Social scientists: A social network is a description of the social structure between actors, mostly individuals or organizations. It indicates the ways in which they are connected through various social familiarities ranging from casual acquaintance to close familial bonds. The term was first coined in 1954 by J. A. Barnes (in: Class and Committees in a Norwegian Island Parish, "Human Relations"). http://en.wikipedia.org/wiki/Social_network “Actors and their actions are viewed as interdependent rather than independent, autonomous units. Relational ties (linkages) between actors are channels for transfer or “flow”of resources… Network models focusing on individuals view the network structural environment as providing opportunities for or constraints on individual action. Network models conceptualize structure (social, economic, political , and so forth) as lasting patterns of relations among actors” (Wassermann, Faust, p.4)

5. What is a network for… Economists: The network effect causes a good or service to have a value to a potential customer dependent on the number of customers already owning that good or using that service. Metcalfe's law states that the total value of a good or service that possesses a network effect is roughly proportional to the square of the number of customers already owning that good or using that service. One consequence of a network effect is that the purchase of a good by one individual indirectly benefits others who own the good - for example by purchasing a telephone a person makes other telephones more useful. This type of side-effect in a transaction is known as an externality in economics, and externalities arising from network effects are known as network externalities. This is also an example of a positive feedback loop. http://en.wikipedia.org/wiki/Network_externality “Interaction and the networks through which it operates are important in determining aggregate economic phenomena and and that this allows us to start from more plausible models of individuals …If this is accepted, then we must first understand how networks influence aggregate outcomes. The next step is to understand how these networks form and if, and why, they persist.” (Kirman, Handbook, 274)

6. What is a network for … Physicists: Complex networks are the backbone of a complex system. They are special networks at the edge of chaos where the degree of connectivity is neither regular nor random. The most complex networks of the real world are either small-world networks or scale-free networks at the border between regular and random networks, between order and randomness. http://en.wikipedia.org/wiki/Complex_network “Recent results on the topology of real networks indicate the emergence of a new paradigm: the apparent randomness of complex systems with many degrees of freedom hides generic mechanisms and order that are crucial to the understanding of the interwoven world surrounding us.” (Barabasi, Handbook, p. 69) Mathematicians: In mathematics, a network is usually called a graph. http://en.wikipedia.org/wiki/Network#Mathematics

7. Struggle among disciplines In all the recent discussions about the relationship between physics and sociology in the study of social networks, the fundamental issue seems to have been lost sight of. The important issue is not whether the two disciplines can or should cooperate. That is essential and it happens frequently. Contributors to the discussion have pointed out many fruitful and important cases, and the history of sociology is full of many others. The big problem arises when academics from one discipline move into the area of another discipline without trying to discover what work has already been done by its practitioners. At best they reinvent the wheel. At worst they antagonise people with their intellectual arrogance. This is what has happened with much of the recent work on small worlds: physicists have argued that their methods and theories can illuminate social networks but have failed to realise that a whole community of sociological network researchers already exists and has done exactly the kind of work that they are pointing to. Their books claim to have made startling discoveries about the social world and advocate the development of new research programmes on these topics. Their reviewers take these claims at face value and so a reputation for intellectual novelty is built up. It is surely a basic failure of normal scholarly research procedures that these books can be written and published without the author undertaking any proper literature search. The author of one recent book expounding the novelty of the 'power law' does not seem to realise that sociological work over many years has documented the existence of this kind of distribution in many real social networks. None of this is cited. Its author does not seem to have discovered the existence of journals on social networks, nor does he seem to realise that INSNA exists and that the cover design of its newsletter shows a network with a power law structure. This same book is based around the author's research into internet search engines, but it doesn't seem as if he has ever typed the words 'social networks' into Google or any other search engine. If I were to come up with the idea that familiar theories from sociology could illuminate problems in physics, the first thing I would do would be a literature search to see if anybody, in physics or elsewhere, had already worked on the issue. Physicists who followed the same strategy when they wished to contribute something to social analysis, might find that they would be welcomed more warmly by their social science colleagues. Posting SOCNET list, 10.2.2005

8. Network as a metaphor • Our aim is to trace different notions of a network in a metaphorical sence across domains of use • We argue that by triangulating various approaches to network as a metaphor, we are able to shed light on the different underlying theoretical and methodological assumptions that sometimes block the possibly fruitful interaction between the different research traditions. • The metaphor of network functions as circulating device (boundary object) across different domains of use

9. Metaphor research • Metaphors are dynamic and flexible tools of translation between different domains • Metaphors often provide a ‘common ground’ concerning terminology and knowledge • In science they might function as heuristic devices helping to generate novel ideas. • Metaphors as (stable) units of circulation between discourses vs. Metaphors as (dynamic) units changing discourses

10. Metaphors in science • Open up common ground for debates (even if the participants of such a debate do not always agree on the meanings of the metaphor) and triggers interdisciplinary discussions • Can be traced by systematically discussing which elements of the metaphor are used in the different domains of use. • Are used in the emergence of new ideas (trading zone).

11. Network as metaphor • To be able to trace “network” as a metaphor we will look at the context and the purpose with which “network” functions as a place holder for different conceptual approaches. • We will discuss the advantages and the limitations of the use of the network in different sc. disciplines or domains of use. • We will introduce dimensions/characteristics of the metaphor network. • We will use these dimensions to differentiate between the different approaches but also to point to possible cross sections between them.

12. How to map the different concepts? Network as a constraint for other dynamic processes (dynamics on networks, dynamics of networked agents) Network evolution as a result of individual actions Network topology as a characteristics of the function of the system Network as a collective phenomena of individual actions Network as a constraint/enabling for individuals

13. Possible dimensions of the network metaphor Large size System Dynamic Collaboration networks over time Scale-free networks Characteristics/structure of a network Network as product of a process Network as function in a process Processes of change, growth and evolution of a network Egonetworks Static Individual Small size

14. Linked metaphors: What is an innovation? ECONOMICS/SOCIAL SCIENCES Innovation is the implementation of a new or significantly improved idea, good, service, process or practice which is intended to be useful. Invention/innovation, radical and incremental innovations, process and product innovation, competition and logistic growth

15. Linked metaphors: What is an innovation? SYSTEMS THEORY Innovation is a critical event which destabilizes the current state of the system and opens a new process of self-organization leading to a new stable state The definition of an innovation bases on the definietion of the borders of the systems (innovation in a firm, innovation in a market), also the emergence of new scientific specialties, new streams of communication, new ways of behaviour are systemic innovations.

16. Linked metaphors: Network and innovation ? • A part of a network? • A new node or a new link? • A new node which destabilizes the whole network (critical event or sensitive networks)? • A product/outcome of a network? • Which type of network? • Which type of relations building the network? • An event of a dynamics taking place on a network topology? • Epidemics on networks -> Criteria for success • Innovations triggering dynamical processes on networks as critical event • Which types of network topologies support innovations?

17. Conclusions 1 • Metaphors can be used to trace the development of new specialties and cross-disciplinary communications. • The network metaphor focuses the attention to the complexity between the parts and the whole. It also allows to address the dualism between structure and action. • While analysing the different context of the network metaphor we determine dimensions of the metaphor in a multidimensional space of meanings.

18. Conclusions 2 • Triangulationin the metaphor space allows to point to hot spots and blind spots in the scientific uses of the network metaphor. • Semantic maps combined with bibliometric analysis (frequency of occupation of areas in the metaphor space) could be a tool to make the space visible.