Fall 2004 Talk Series on
Networks and Complex Systems
Every Monday 6-7p, LI 001 ~ Optional Dinner Afterwards
This talk series is open to all Indiana University faculty and students
interested in network analysis, modeling, visualization and complex systems
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
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.
Katy Börner <firstname.lastname@example.org> 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
9/13 Stanley Wasserman,
Sociology & Psychology Department, IUB
Why Should I Care about Social Network Enterprise Software?
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 ...
Vespignani, School of Informatics, IUB
Modeling: Dealing with Complexity
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
Janssen, School of Informatics and Center for the Study of Institutions,
Population, and Environmental Change, IUB
in Social-Ecological Networks: The Case of Irrigation on Bali
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 ...
M. Beggs, Physics Department, IUB
Properties in Local Networks of Cortical Neurons
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
as Crucial Connectors in Networks
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 ...
Yaeger, School of Informatics, IUB
Neural Network Architectures in a Computational Ecology
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
Sporns, Psychology Department, IUB
Development, and Function of Complex Brain Networks
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 ...
Redner, Department of Physics, Boston University & Center for
Nonlinear Studies, Los Alamos National Laboratory
Physics of Popularity-Driven Networks
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
Alison Bryant, Telecommunications, IUB
Community Ecology through Network Analysis
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
Schnell, School of Informatics, IUB
Unraveling the Biochemical Reaction Kinetics from Time-Series Data
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.
Haythornthwaite, SLIS, University of Illinois at Urbana-Champaign
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
Menczer, School of Informatics and Department of Computer Science,
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.
DeYoe, Medical College of Wisconsin
The Expression and Control of Attentional Topography
in Human Visual Cortex 4pm, Room 101, Psychology
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.
Wuchty, Department of Physics, University of Notre Dame
clustering and evolutionary conservation of protein-protein
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
This talk series continues in Spring