NETWORKS Match Maker Seminar

Please check the website for all information and registration NETWORKS Match Makers Seminar (networksmatchmaking.nl)

Everyone who is interested is invited to participate, but we would like to ask you to register.

Register now! (registration is handled by Leiden University)

Programme:

CEO and founder at wallet79

Toward a General Theory of Organizing – Introducing the Network Field Model

We lay the foundation for a general theory of organizing. We propose that organizing is a continuous process of ongoing mutual or reciprocal influence between objects (e.g., human actors) in a field, whereby a field is infinite and connects all the objects in it much like electromagnetic fields influence atomic and molecular charged objects or gravity fields influence inanimate objects with mass such as planets and stars. We use field theory to build what we now call the Network Field Model. In this model, human actors are modeled as point-like objects in the field. Influence between and investments in these point-like human objects are explained as energy exchanges (potential and kinetic) which can be described in terms of three different types of capital: financial (assets), human capital (the individual) and social (two or more humans in a network). This model is predicated on a field theoretical understanding about the world we live in. Using the model we are able to describe different social-economic effects in networks such as the governance and exchange rules in different markets.

Ben Meylahn
University of Amsterdam

We consider the problem of opinion formation as one of trust and learning. The reliability of an opinion is the fraction of life’s experiences it agrees with. By assuming that agents follow a satisficing decision-making rule with a threshold influenced by the opinions held by their neighbours, we are able to design a model for how opinions may change over time in a network of sophisticated agents. This model doesn’t assume that opinions are simply a product of one’s friends and connections but includes a sophisticated mechanism by which these still play a role, in combination with an independent learning procedure. The model is to be presented with preliminary results.

General

Over the past decade, multiple scientific disciplines have contributed to the understanding of how highly complex systems operate, with an increasing interest in synergies. The social sciences have provided insight into the structure of social entities and have developed theories explaining the patterns that are observed. The economic sciences have offered a perspective on how the behaviour by people is shaped by incentives and by their expectations about the behaviour of others. Computer science and mathematics have built a framework and a toolbox for explaining and quantifying the complexity that is encountered in various settings. This intriguing blend is part of a new research area under the name of network science, with a focus on explaining complex phenomena in social, economic and technological systems, and beyond.

Organizers: Frank den Hollander (Leiden University), Ines Lindner (Tinbergen Institute, research master Business Data Science and Vrije Universiteit Amsterdam), Michel Mandjes (University of Amsterdam)