Spring 2006 Talk Series on
Networks and Complex Systems
Every Monday 6-7p, Wells Library LI001 ~ Optional Dinner
at at Lennie's
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, research
in 'hard core' sciences such as biology or physics,
but also research on Internet technologies.
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.
Katy Börner <email@example.com> Associate Professor
of Information Science, SLIS, IUB.
Time & Place
Every Monday 6:00-7:00pm in the Wells
Library LI 001 (formerly Main Library), Indiana University, Bloomington.
Right after the Cognitive
Science Colloquium Series. There is an optional dinner afterwards 7-9p
Students interested to attend the talks for credit need to register for
(1 credit) with Katy Börner.
Proposal form is here.
Grading will be based on the attendance of 8 talks (sign-up sheets will
be provided) and a 4-5 page write-up that synergizes/aggregates major points
made by a subset of the speakers to be submitted at the end of the semester.
Evolving list of recommended readings. See
also the Wikipedia entries on graph
world networks, power
law, and complex
networks, and self
Colloquium on Complexity and Social Networks organized by Davin Lazer
1/16 M. L. King, Jr. Day
Bradford Paley, Digital Image Design Incorporated / Columbia University
Supporting Visual Analysis: Perceptual, Cognitive, and Semantic Techniques
Abstract: W. Bradford Paley has deployed work in
seemingly diverse settings: the Museum of Modern Art, the New York Stock Exchange,
NYU Bioinformatics, the Whitney; he has won equally diverse recognition: an
ID Design Distinction award, Grand Prize in Tokyo's international arts festival,
engineering tool awards for input devices, fellowship in the New York Foundation
for the Arts. The same principles drive all of this work: If you engage the
eye, you can engage the mind--as long as you "know the protocol,"
and keep the message consistent.
This talk has two parts. The first part will describe a knowledge acquisition
pipeline: A designer/engineer's abstraction of visual, cognitive, and semantic
"protocols" that engage seven distinct layers of the visual thinking
processes. The second part introduces numerous examples of Mr. Paley's work
informed by these protocols. Among them are the artwork TraceEncounters
which is becoming a social network analysis tool for use by real researchers;
the Whitney-commissioned CodeProfiles has been mistaken for a debugging tool;
the Structualist text analysis tool TextArc
was "mistaken for art" and won the Tokyo New Media Festival's grand
1/30 Harold D. Green, Jr., Science
of Networks in Communities (SONIC) Research Group, National Center for Supercomputing
Applications, University of Illinois at Urbana-Champaign
Artistic, Cultural, and Network Assets in the Chicago Metropolitan Area: Context,
Project Design, Implementation, and Initial Findings
Abstract: The Chicago metropolitan area has, for
the past few years, become a key destination for Mexican transnationals, both
temporary and permanent. Post-NAFTA Mexican immigrants have combined their
cultural, artistic and network resources to create hybrid behavioral and cultural
forms unlike those commonly used in America or Mexico. The use of these hybrid
forms allows migrants to leverage their social and cultural resources to gain
access to basic assistance, jobs, social support services, and other types
of group-based or group-facilitated resources. This study was conducted in
conjunction with the Field Museum in Chicago. It combined innovations in ethnographic
research—such as the use of Atlas Ti and other ethnographic support
tools—with new techniques for egocentric social network data collection
that incorporate electronic data collection and one-touch network discovery
capabilities, to delve more deeply into the realities of life for the Mexican
immigrant community. In the process, aspects of the widely popular ‘network
theory of migration’ are investigated in more detail than has been previously
possible. In this talk, I present the motivations for the project, identify
the factors that led to the synthesis of ethnography and social network analysis,
explain the new approaches that the research team developed and, finally,
present some initial findings from the project, calling attention to how those
findings correspond to current thinking vis-à-vis ‘network theory
of migration’ and to the current immigration policy environment.
Gregor, SoI, IUB
Large-Scale Network Analysis with the Boost Graph
Abstract: In recent years, our ability to collect
network data has increased far beyond our capabilities to analyze this data.
With this deluge of data, the simple, direct implementations of network analyses
and data structures no longer suffice, and we must turn to more advanced techniques
such as graph compression and parallel computing. This talk will introduce
the Boost Graph Libraries,
a set of libraries for graph and network analysis developed by the Open Systems
Lab at Indiana University. The Boost Graph Libraries provide a consistent
set of interfaces across the entirety of the productivity--performance spectrum,
from the rapid-prototyping and visualization capabilities of
BGL-Python, to the high-performance sequential BGL and cluster-capable Parallel
BGL. This talk will explore the relative merits of each library, to determine
which BGL may be right for your network analysis task, regardless of whether
your network is measured in tens, thousands, millions, or billions.
2/13 Tamara Munzner, Department of Computer Science, University of British Columbia
Scalable Visual Comparison of Biological Trees and Sequences
Abstract: We present the TreeJuxtaposer
visualization applications for comparing and browsing evolutionary trees and
genomic sequences, respectively. These systems use the Focus+Context navigational
metaphor of allowing users to fluidly stretch and shrink parts of the view,
as if manipulating a rubber sheet with the borders tacked down. We introduce
cognitive scalability to this approach by guaranteeing the visibility of landmarks
at all times, so that users can stay oriented as they explore complex datasets.
In our systems, landmarks can be regions of difference between datasets, or
the results of a search, or user-chosen regions. This technique, which we
call "accordion drawing", supports smooth realtime transitions between
a big-picture overview and a drilled-down views that show details in context.
Our new PRISAD infrastructure
is highly scalable, allowing fluid realtime interaction with trees of several
million nodes and multiple aligned sequences of up to 40 million total nucleotides.
Goldstone, Department of Psychological and Brain Sciences, and Program
in Cognitive Science, Indiana University
The Propagation of Innovations in a Social Network
Abstract: We have developed an internet-based experimental
platform (for examples, see
that allows groups of 2-200 people to interact with each other in real time
on networked computers. I will describe experiments using this platform that
explore how people attempt to solve simple problems while taking advantage
of the developing solutions of other people in their social network. Over
15 rounds of problem solving, participants received feedback not only on the
success of their own solutions to a simple search problem, but also on their
neighbors¹ solutions and outcomes. Neighbors were determined by one of
four network topologies: locally connected lattice, random, fully connected,
and small-world (e.g. a lattice plus a few long-range connections). The results
suggest that complete information is not always beneficial for a group, and
that problem spaces requiring substantial exploration may benefit from networks
with mostly locally connected individuals. We model the dissemination of innovations
in these experiments using agents that probabilistically select choices guided
by their own and their neighbors' explorations.
Yaeger, School of Informatics & Olaf
Sporns, Department of Psychological and Brain Sciences, Indiana University
Evolution of Neural Complexity
Abstract: We analyze evolutionary trends in artificial neural dynamics and network architectures
specified by haploid genomes in the Polyworld computational ecology. We discover consistent trends in neural connection densities,
synaptic weights and learning rates, entropy, mutual information, and an information-theoretic measure of complexity. In particular,
we observe a consistent trend towards greater structural elaboration and adaptability, with a concomitant and statistically significant
growth in neural complexity.
Statistics, Sociology, and Psychological and Brain Sciences,
Statistical Analysis for Network Science
Abstract: This talk highlights the wide range of statistical analyses that are part of network science. Of particular importance are the exponential family of random graph distributions, known as p*, and recent work on robustness and resistance of network data when actors and/or relational ties are missing or removed.
3/13 - 3/17 Spring Break
Hargittai, Northwestern University -
Talk was cancelled.
Cross-Ideological Discussions among Top Conservative and Liberal Bloggers
Abstract: Information technologies make both interpersonal
and one-to-many communication easily accessible to users having led to many
speculations about their potential for influencing political communication.
This paper explores the extent to which contemporary online political discussions
on blogs have a cross-ideological component. Through a look at the interactions
among the most popular conservative and liberal blogs, the paper considers
whether authors representing opposing ends of the ideological spectrum engage
each other in conversation. An analysis of linkages among such blogs sheds
light on whether people of different political persuasions participate in
any idea exchange online. The paper tests hypotheses about fragmentation and
looks at whether widespread use of the Internet encourages dissenting political
views to flourish or whether the Web merely offers a safe haven for everyone
by isolating people with different opinions from each other.
R. Heise, Sociology, Indiana University
Delineating Social Institutions From Semantic Networks
Abstract: Dictionary definitions provide an accessible
and commonsense body of data describing the cultural understandings that individuals
have about role-identities. This research analyzes cross-references between
definitions of several hundred identities to see whether social institutions
can be viewed as confluences of identity meanings. I created a zero-one adjacency
matrix by linking identities to the concepts given in their definitions. I
then computed boolean powers of the adjacency matrix to simulate the process
of looking up words that definitions contain. Principal components analysis
of the result organized identities into clusters corresponding to standard
social institutions, like family, education, medicine, work, law, religion.
The analysis sub-divided some standard institutions in interesting ways, and
additionally it identified sexuality as an incipient social institution.
Fortunato, SoI, Indiana University
Egalitarian Search Engines
Abstract: Search engines have become key media
for our scientific, economic, and social activities by enabling people to
access information on the Web in spite of its size and complexity. On the
down side, search engines bias the traffic of users according to their page-ranking
strategies, and some have argued that they create a vicious cycle that amplifies
the dominance of established and already popular sites. We show that, contrary
to these prior claims and our own intuition, the use of search engines actually
has an egalitarian effect. We show that the search behavior by users mitigates
the attraction of popular pages, directing more traffic toward less popular
4/10 Aonan Tang & John
Beggs, Physics, Indiana University
cortical networks: Functional topology and dynamics
Abstract: The average cortical neuron makes and receives about 1,000 synaptic contacts. This anatomical information suggests that local cortical networks are connected in a fairly democratic manner, with all nodes having about the same degree. But the physical connections found in the brain do not necessarily reveal how information flows through the network. Here we will describe our ongoing work to uncover functional connectivity from living networks of cortical neurons in vitro. We use both acute cortical slices and cortical slice cultures which can be kept alive for periods of about 10 hrs. Our first experiments with 60-channel microelectrode arrays did not allow us to get a clear picture of functional network topology. Our more recent work with a 512 electrode array system (in collaboration with Alan Litke of UC Santa Cruz) has allowed us to overcome many of these initial difficulties. We have also made improvements in the way we measure information transfer between recording sites. We will present these new results and discuss the implications they have for cortical information processing.
Alessandro Flammini, SoI, Indiana University
A Simple Approach to Species' Lifetime Distribution in Ecology
Abstract: Since the seminal work of Lotka and Volterra,
Ecology has offered the inspiration to several unsophisticated yet insightful
approaches that found thereafter a ready application to the more general field
of Complex Systems. Strong of this excuse, we address with a zero-th order
evolutionary model the issue of taxa's lifetime distribution. Altough the
model is simple enough
to be exactly solvable and makes no specific assumptions on the pattern of
interaction between species, it offers a natural explanation to several, apparently
conflicting, empirical data collections.
C. North, AT&T Labs
Abstract: Measuring distance or some other form of proximity between objects is a
standard data mining tool. Connection subgraphs were recently proposed
as a way to demonstrate proximity between nodes in networks. We propose
a new way of measuring and extracting proximity in networks called "cycle
free effective conductance'' (CFEC). Our proximity measure can handle
more than two endpoints, directed edges, is statistically well-behaved,
and produces an effectiveness score for the computed subgraphs. We provide
an efficient algorithm. Also, we report experimental results and show
examples from several collaboration and communication networks.
The proposed method usually produces results that are readily visualized.
We plan to continue this talk series in Fall 2006.
Please contact Katy Börner
if you are interested in presenting.