Objectives

The objective of this project is:

1. to develop new methods to recognize emerging critical events in evolving complex networks, coupled networks and active agent networks
2. to apply these methods to the analysis of the emergence of new research topics (scientific avalanches)  and possible crises in a social institution – the public trust in science.

Motivations or why do we want to work on this project?

The aim of the project
The aim of the project is, based on a new and innovative understanding of critical events in mediated social networks, to develop policy recommendations with regard to scientific avalanches and public understanding of science.
 
Why critical events?
We want to study emerging crises in complex networks and multi- networks that can lead to drastic changes in the whole system. Although there are a lot of new results concerning the structure of evolving networks in the sense of their geometrical properties (Dorogovtsev & Mendes, 2003; Bornholdt & Schuster (Eds.), 2002), the dynamics and critical properties of these systems are almost unknown. Even for such a simple system as the Ising spin model mapped onto the Barabasi-Albert network (Barabasi & Albert, 1999) amazing effects occur because the critical temperature in this system diverges in the thermodynamical limit to infinity with log(N), where N stands for the number of nodes in the network (Aleksiejuk et al., 2002).

It is important to stress that a network entering into the critical region exhibits large scale fluctuations and is very sensitive to presence of external fields. It follows that the stability of such a  network changes dramatically what can be especially crucial for social systems.

Where do critical events appear in real social networks?
We focus in this project on social networks and more particularly on the spreading of information in scientific and public communication networks. We see as critical events the emergence of information avalanches linked to the emergence of a collective behaviour in large groups of social actors. In science scientific avalanches can represent the emergence of new research topics that rapidly attract large parts of the scientific community. In this case one would like to understand how to trigger such critical events which lead to an innovation in the system. There are other cases where information avalanches occur as a panic-like reaction which destabilizes the system. The dynamics of public trust in science gives examples of regularly occurring avalanches.

What kind of networks and what kind of actors? 
Social networks are characterized by the ambiguity of the actors involved (Newman, 2004). Human beings are able to participate in many networks, acting in different roles, at the same time (Watts et al., 2002). In a real situation isolated networks almost do not exist. One problem in the application of abstract graph theoretical models to social systems is therefore the appropriate definition of the nodes (actors or agents) and of the processes creating links between them.
                   If one considers information flows in communication networks than it is evident that different networks interrelate with each other. In system theory scientists communicate in certain circles (journals or invisible colleges) using a certain code (scientific articles), whilst in the public media journalists follow other rules in their communication behavior. However, scientific innovation often appears at the boundaries of certain specialties in science, combining different scientific discourses. The public perception of science emerges at the boundary between science communication and public communication, both often interwoven.
                   Therefore, the issue of systems consisting of many coupled networks is very important for the analysis of social phenomena. Theoretically, on the level of abstract complex networks the question is not yet solved. This project aims to overcome this gap.
                   A theoretical and numerical description of multi-network systems will be created. Internal variables will be localized at networks nodes to describe dynamics of corresponding agents.  Cases of a symbiosis and of a competition between different networks will be considered. Static and dynamical properties of such systems will be analyzed with the aid of analytic methods as the mean field approach and will be compared to results of numerical simulations.
                   As a special case one can consider the influence of external forces on a network. With this, the influence of the second network on the first one will be expressed in terms of an overall acting driving force.
                   Empirically, we will identify different actors and the networks they are involved in, in a given scientific debate and its public perception. One can find very different representations of communication processes and accordingly social scientists have produced many complementary descriptions of communication processes. Examples are media theory, communication and information theories, and sociology. In the project our empirical description will be in social science terms but guided by concepts of the physics of complex networks. This way we can create a projection of social structures which are complex but not complicated.
                   Beside network structures another approach in complexity science seems to be very relevant in modeling social phenomena. Recently, the notion of active agents has been introduced to describe a special kind of collective phenomena. In this case, the structures occur because of non-linear interactions between the agents which are able to additionally influence the interactions by themselves (Schweitzer, 2003). This possibility of self-determination is in particular suitable for social processes where the individuals have to balance between their own motivations driving their actions and the social constraints creating the boundary conditions for their actions.
                   Summarizing, one can identify three cases which seem to be particularly relevant for describing mediated social communication and where a combination of complexity research and social science research seems to be especially fruitful:
- dynamical processes on coupled complex networks
- the influence of external forces on complex networks
- active agents(actors) in complex networks

Project strategy

This project aims to combine concepts and descriptions from social and information sciences with concepts and description from physics. Instead of proposing another “application” of complexity research to social systems we will develop a common view informed by different research traditions. This has consequences for the research strategy necessary to reach such a goal. It requires in particular the developing of a common language.

We will link in our analysis three different research approaches crossing disciplinary boundaries:

1. a social science perspective of public trust in science as an example of a social institution (qualitative model)
2. quantitative approaches to make dynamic processes in networks of communication visible (data mining and visualization)
3. an analytical framework developed in statistical physics to understand emergent phenomena in complex networks (mathematical model) supported by numerical simulations and an active agents approach

                   The project places itself on the edge of different research fronts. Concerning the theoretical description of complex networks it asks for models of the emergence of critical events in complex networks disturbed by external forces and coupled to each other. Concerning the empirical evidence of critical events in social communication networks it ask for the operationalization of mediated communication in terms of networks of actors and topics and the possibilities of automated data mining from the web and other sources to reconstruct these network structures. Concerning the analysis of empirical representations it asks for new visualization tools which allow to representation of dynamic events and algorithms to calculate changing network properties over time. Concerning the control of critical events in real networks it ask for policy recommendations informed by complexity approaches.

                   The challenge of the project, given its broad-range inter-disciplinarity, is to create a common area of understanding (“trading zone”) where models of information avalanches in mediated networks developed in communication theory, media theory, and science and technology studies, probabilistic models of data mining in complex networks and mathematical models about the evolution of complex networks can communicate with each other.