Fall 2004 Talk Series on

Networks and Complex Systems

Every Monday 6-7p, LI 001 ~ Optional Dinner Afterwards

Description
This talk series is open to all Indiana University faculty and students interested in network analysis, modeling, visualization and complex systems research.

A major intent is to cross-fertilize between research done in the social and behavioral sciences and research in 'hard core' sciences such as biology or physics.

Links to people, projects, groups, students, courses and news related to complex systems and networks research at Indiana University are also available via the CSN web site.

  •    The slides of all talks will be be available online.
  •    Most talks will be video taped.

Organizer
Katy Börner <katy@indiana.edu> Assistant Professor of Information Science, SLIS, IUB.

Time & Place
Every Monday 6:00-7:00pm in the Main Library LI 001, Indiana University, Bloomington. Right after the Cognitive Science Colloquium Series.

There is an optional dinner afterwards 7-9p at Lennie's.

This talk series continues in Spring 2005.

9/13 Stanley Wasserman, Sociology & Psychology Department, IUB

Why Should I Care about Social Network Enterprise Software?

Abstract:
This talk, which could be subtitled "What I Did on my Summer Vacation", describes scientific work at VisiblePath Corporation, in New York City. VisiblePath's approach to social network analysis in the enterprise is based on four core tenets (taken directly from http://www.visiblepath.com):

1. Social networks are complex.
Typical corporate networks are millions of times as complex as a simple social network structure.
Complexity is a function of robust attribute data on the nodes (people), multiple relations and links between nodes, valued relations, degradation of relations over time, and the breadth and density of enterprise networks, where typical networks include tens of millions of relations between millions of nodes. Read more ...

9/20 Alessandro Vespignani, School of Informatics, IUB

materials iconmaterials iconEpidemic Modeling: Dealing with Complexity

Abstract:
The mathematical modeling of epidemics is a very active field of research that crosses different disciplines. Epidemiologists, computer scientists and social scientists share a common interest in studying spreading phenomena and make use of very similar models for the description of the diffusion of viruses, knowledge and innovation. Epidemic modeling relies also on the knowledge of the underlying population structure in which the spreading is occurring. In this perspective, the increased power of computers and informatics tools is having a large impact on epidemic modeling by allowing the gathering and handling of large data sets for a variety of contact networks of practical interest in social science, critical infrastructures and epidemiology. Read more ...

9/27 Marco Janssen, School of Informatics and Center for the Study of Institutions, Population, and Environmental Change, IUB

materials iconCoordination in Social-Ecological Networks: The Case of Irrigation on Bali

Abstract:
Various local and regional social-ecological systems (SES's) have existed for hundreds of years, remaining in particular configurations that have withstood a variety of natural and social disturbances. What enabled these systems to persist? Many long-lived SES's have adapted their institutions to the disturbance and stress regime they have experienced over time as well as to the broader economic, political, and social system in which they are located. Such adaptations change the use of resources in time and/or space to maintain the desired configuration of the SES's.Read more ...

10/4 John M. Beggs, Physics Department, IUB

materials iconmaterials iconEmergent Properties in Local Networks of Cortical Neurons

Abstract:
The cerebral cortex has expanded rapidly in the evolution of mammals and is essential for higher cognition. Despite a surface area of nearly 2500 cm2, human cortex remarkably seems to be composed of many similar modules, each ~0.5 cm2 and containing about 150,000 neurons. Each module receives information from other modules, performs some operations, and passes the results on to other modules. But how do these modules themselves process information? Read more ...

10/11 Scott Feld, Sociology Department, Purdue University

materials iconmaterials iconGroups as Crucial Connectors in Networks

Abstract:
This paper shows how basic properties of inequality in directed networks have systematic implications for connectedness in networks. We specifically show how four particular properties of inequality in directed networks are related to the frequencies of various types of indirect connections. Read more ...

10/18 Larry Yaeger, School of Informatics, IUB

materials iconmaterials iconEvolving Neural Network Architectures in a Computational Ecology

Abstract:
Profound evidence exists to demonstrate wide-spread, general plasticity and learning in biological brains, yet equally clearly the "wiring diagram" of the brain matters. Key attributes of brain function and form have been shown to be well modeled by Hebbian learning in artificial neural networks (ANN's) with suitable network architectures. I will discuss an artificial life system designed to evolve highly arbitrary ANN architectures, which then employ Hebbian learning, in a computational ecology. Read more ...

10/25 Olaf Sporns, Psychology Department, IUB

materials iconmaterials iconOrganization, Development, and Function of Complex Brain Networks

Abstract:
Recent research has revealed general principles in the structural and functional organization of complex networks which are shared by various natural, social and technological systems. This talk examines these principles as applied to the organization, development and function of complex brain networks. Read more ...

11/1 Sidney Redner, Department of Physics, Boston University & Center for Nonlinear Studies, Los Alamos National Laboratory

materials iconmaterials iconStatistical Physics of Popularity-Driven Networks

Abstract:
The rate equation approach is applied to quantify basic features of growing, popularity-driven networks. A prototypical example is the network of citations associated with scientific publications. Basic empirical facts about the citation network will be presented, based on the entire corpus of Physical Review publications from the past 110 years. Read more ...

11/8 J. Alison Bryant, Telecommunications, IUB

materials iconmaterials iconUnderstanding Community Ecology through Network Analysis

Abstract:
Recent work in organizational change has highlighted three opportunities for future investigation - the need to understand organizational evolution from the level of the community; the need to more systematically understand the complex relationships within the community; and the need to incorporate network analysis in the study of community ecology. Read more ...

11/15 Santiago Schnell, School of Informatics, IUB

materials iconmaterials icon Unraveling the Biochemical Reaction Kinetics from Time-Series Data

Abstract:
Time course data can now be routinely collected for biochemical reaction pathways, and recently, we are proposing several methods to infer reaction mechanisms for metabolic pathways and networks. In this talk we provide a survey of techniques for determining reaction mechanisms for time course on the concentration or abundance of different reacting components, with little prior information about the pathways involved.

11/22 Caroline Haythornthwaite, SLIS, University of Illinois at Urbana-Champaign

materials iconmaterials iconComputer-Mediated Social Networks

Abstract:
The near ubiquitous use of computer media has stirred controversy about what is appropriate, possible, and efficient to do via these media. While many studies have looked at what use is made of CMC, studies have mainly examine aggregate views of single media, for example, looking at how email, bulletin boards, or blogs are used. This ignores the very real role of interpersonal ties on media use and relational maintenance, and the way multiple media support ties and group interactions. Read more ...

11/29 Filippo Menczer, School of Informatics and Department of Computer Science, IUB

materials iconmaterials iconWeb Networks

Abstract:
This talk will describe ongoing efforts to study the topological and dynamical properties of link, lexical, and semantic networks stemming from various features of the World Wide Web. I will outline what we think, what we know, what we can use regarding the structure and content of the Web, and what the future of intelligent Web search may bring.

12/6 Edgar DeYoe, Medical College of Wisconsin

The Expression and Control of Attentional Topography in Human Visual Cortex 4pm, Room 101, Psychology

Abstract:
Using fMRI it has been possible to study how attention spatially modulates visual processing in the occipital lobe under various stimulus and task conditions. However, this does not account for how other areas, such as fronto-parietal cortex, may control these attentional effects. In a series of experiments, we examined the topographic representation of attended locations in both occipital and parietal cortex in order to understand better how the expression of spatial attention and its control are interrelated. Read more on the CogSci Colloquium Series page.

12/13 Stefan Wuchty, Department of Physics, University of Notre Dame

 materials iconRobustness, clustering and evolutionary conservation of protein-protein
interactions

Abstract:
Contemporary genomics and proteomics tries to elucidate the webs of protein-protein interaction networks of various organisms. A critical goal of the network paradigm thus emerging is the potential for application of these principles to understand and make predictions about biological systems. Yet, the severe error proneness of methods to elucidate protein-protein interactions casts doubt on the general usefulness of the resulting topologies. Modeling the high error rates in the determination of both protein-protein interactions and orthologous proteins in yeast, we find that the originally reported
trends on the preferential evolutionary conservation of highly interacting proteins and cohesive groups of proteins are robust. Read more ...

This talk series continues in Spring 2005.