Fall 2005 Talk Series on

Networks and Complex Systems

Every Monday 6-7p, I 106 ~ Optional Dinner at at Lennie's 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, 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.

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

Time & Place
Every Monday 6:00-7:00pm in the Informatics Building@IUB, 901 E. 10th St., Room 107. Right after the Cognitive Science Colloquium Series. There is an optional dinner afterwards 7-9p at Lennie's.

Credit
Students interested to attend the talks for credit need to register for L600 (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.

Previous Talks
Fall 2004
Spring 2005

Evolving list of recommended readings. See also the Wikipedia entries on graph theory, small world networks, power law, and complex networks, and self organizing systems.

Related series
Cambridge Colloquium on Complexity and Social Networks organized by Davin Lazer at Harvard.

8/29 Faculty, Indiana University Bloomington

materials iconOverview of Network & Complex Systems Courses at IUB

P582 Biological and Artificial Neural Networks by John Beggs, Physics
Artificial Life as Approach to AI
by Larry Yaeger, Informatics
INFO-I 400/590 Biologically Inspired Computing by Luis Rocha, Informatics
The Simplicity of Complexity
by Alessandro Vespignani & Alessandro Flammini, Informatics
TEL603: Communication Networks by J. Alison Bryant, Telecommunications
400/590 Structure of Information Environments by Peter Todd, Psychology & Informatics
CSCI B538 Computer Networks by Minaxi Gupta, Computer Science
L597 Structural Data Mining & Modeling by Katy Börner, SLIS
Networks & Complex Systems
talks Katy Börner, SLIS

9/05 Labor Day

9/12 Alessandro Vespignani & Katy Börner, Indiana University

materials iconmaterials iconNetwork Science: A Theoretical and Practical Framework

Abstract: The first part of this talk presents a theoretical framework for network science as a basis for the comparison and integration of the many different techniques and algorithms developed in mathematics, statistics, physics, social sciences, bibliometrics/scientometrics, and other scientific disciplines. The second part of the talk provides an overview of network measurement and visualization techniques as a means to increase our understanding of the structure and dynamics of networks. We conclude with a discussion of opportunities and challenges for network science. Read more ...

9/19 Vittoria Colizza, Indiana University.

materials iconmaterials iconAre global epidemics predictable?

Abstract: We present a stochastic computational framework for the forecast of global epidemics that considers the complete world-wide air travel infrastructure complemented with census population data. Here we address two basic issues in global epidemic modeling: i) We study the role of the large scale properties of the airline transportation network in determining the global diffusion pattern of emerging disease; ii) We evaluate the reliability of forecasts and outbreaks scenarios with respect to the intrinsic stochasticity of disease transmission and traffic flows. In order to address these issues we define a set of novel quantitative measures able to characterize the level of heterogeneity and predictability of the epidemic pattern and its relation with the network's structure, These measures may be used for the analysis of containment policies and epidemic risk assessment.

9/26 Robert Goldstone, Department of Psychological and Brain Sciences, and
Program in Cognitive Science, Indiana University

materials iconThe Paths that Groups Make

Abstract: Just as ants interact to form elaborate colonies and neurons interact to create structured thought, groups of people interact to create emergent organizations that the individuals may not understand or even perceive. My laboratory has begun to study the emergence of group behavior from a complex adaptive systems perspective. We have developed an internet-based experimental platform (for examples, see http://groups.psych.indiana.edu/) that allows groups of 2-200 people to interact with each other in real time on networked computers. Agent-based computational models are used as accounts of the experimental results. Read more ...

10/3 Ikuho Yamada, Department of Geography and School of Informatics Indiana University - Purdue University, Indianapolis

materials iconmaterials iconHot Spot Detection in a Network Space: Geocomputational Approaches

Abstract: Because human activities are highly dependent on transportation networks, various spatial phenomena are also conditioned or constrained by the networks. For example, vehicle crashes occur only on the streets and crime locations geocoded with a street address system are basically all on the streets. Though analyzing clustering tendency and detecting clusters (or hot spots) is a good starting point to understand a spatial phenomenon and further to make decisions on controlling the phenomenon or related human activities, analytical methods designed for a planar space are likely to yield biased results leading us to inappropriate decisions. Read more ...

10/10 Steven A. Morris, Oklahoma State University

materials iconmaterials iconManifestation of Research Specialty Processes in Collections of Journal Papers

Abstract: A research specialty is a self-organized social organization whose members tend to study a common research topic, attend the same conferences, publish in the same journals, and belong to the same "invisible colleges." Research specialties create their on body of literature, and a "collection of papers" is defined as a comprehensive sample of such a body of literature. Read more ...

10/17 Armin P. Moczek, Biology, Indiana University.

materials iconmaterials icon Integrating micro-and macroevolution of development: A case study on horned beetles

Abstract: A fundamental goal of evolutionary biology is to understand how ecological, developmental and genetic processes interact in the genesis of novel phenotypic traits. My research addresses this question by studying the ecological, developmental, and genetic underpinnings of a dramatically diverse class of traits: beetle horns. Several thousand species of beetles have evolved horns or horn-like structures, and a remarkable diversity of horn phenotypes exists both below and above the species level. At the same time beetle horns are unique, novel structures that lack obvious homologues in other taxa. In the first part of my presentation I will explore the behavioral and ecological context in which beetle horns function and evolve, and the developmental mechanisms that mediate morphological diversification in horn expression on the level of populations. In the second half I will then explore how understanding the developmental genetic regulation of horn expression can provide important insights into the ancestry of horns, as well as the mechanisms that enabled the diversification of horn phenotypes on different levels.

10/24 Tanya Berger-Wolf, Department of Computer Science, University of Illinois at Chicago

materials iconmaterials icon A Computational Framework for Analysis of Dynamic Social Networks

Abstract: Finding patterns of social interaction within a population has wide-ranging applications including: disease modeling, cultural and information transmission, phylogeography, conservation, and behavioral ecology. Scientists have successfully modeled social interaction with networks. One of the intrinsic characteristics of societies is their continual change. However, majority of the social network analysis methodologies today are essentially static in that all information about the time that social interactions take place is discarded or long time series are averaged to discern the overall or long-term strength of connections. Such approach not only may give inaccurate or inexact information about the patterns in the data, but it prevents us from even asking questions about the temporal causes and consequences of social structures. I will present a new mathematical and computational framework that allows analysis of dynamic social networks addressing the time component explicitly.

10/31 Happy Halloween!

11/07 Peter Todd, Informatics, Cognitive Science & Psychology, Indiana University

materials iconmaterials icon When to get married: From individual mate search to demographic marriage patterns

Abstract: The choice of a partner for marriage or cohabitation is one of the key events in the course of our lives. But the scientific study of marriage is typically pursued by two single research traditions that themselves should be wedded: demographic research with data on aggregate population-level patterns such as age at marriage and proportion ever marrying, and psychology and economics with models of the (often heterogeneous and culturally varying) individual-level processes that can end in the decision to cohabit or marry. How can the former top-down macro perspective and the latter bottom-up micro view be brought together to speak to each other? Read more ...

11/14 Matthew Hahn, Biology, Indiana University.

materials iconmaterials icon Evolution in genetic networks

Abstract:
Proteins do not evolve in isolation, but rather as components of complex genetic networks. Therefore, a protein’s position in a network may indicate how central it is to cellular function, and hence how constrained it is evolutionarily. We have examined the protein-protein interaction networks in yeast, worm, and fly, and have found that proteins with a more central position in all three networks—regardless of the number of direct interactors—evolve more slowly and are more likely to be essential for survival. By studying various types of genetic networks in a number of different genomes, we can begin to understand the determinants of sequence evolution—and therefore of phenotypic evolution.

11/21 Fabio Rojas, Sociology, Indiana University

materials icon Discipline in Formation: Networks Among Black Studies Professors

Abstract: This paper examines social networks among Black Studies professors. I show that Black Studies is a remarkably open academic discipline. Black Studies professors are most likely to maintain academic contacts with persons outside their programs and discipline. After documenting this basic fact about Black Studies networks, I example the effects of ego-centric network content on academic behaviors and attitudes. I will discuss the importance of the results for the study of academic disciplines.

11/28 Bernice Pescosolido, Sociology, Indiana University

materials iconmaterials icon The Role of Sociology and Social Networks in Integrating the Health Sciences

Abstract: Over the last five or so years, a series of reports from the National Academy of Sciences and the National Institutes of Health, among others, have issued a call for integrating the biomedical sciences (BMS) and socio-behavioral sciences (BMS). While many approaches have been offered over the last 30 years to join the insights of different disciplinary projects together, all have failed to take hold. This presentation reviews those calls and attempts, raising the potential of social network perspective to fill the gap. Based on the example of models of the causes and consequences of the onset of illness/disease, the presentation follows the development of one network-based platform and ends with epistemological questions about future research.

12/05 James Moody, Sociology, The Ohio State University

materials iconmaterials icon The Network Model of Sociological Production

Abstract: This talk is the first part of a much larger project on the evolution and dynamics of scientific fields. The long-term motivation for this work is to provide a "satellite" image of the evolution of scientific fields that will help us pinpoint the life-history of "good ideas." In this talk, I take sociology as a case study and describe the evolution and structure of sociological production networks from 1965 to the present. This work moves across citation, coauthorship and "topic" networks to provide a composite image of changes in the field over the last 40 years. I then link these findings substantively to questions about scientific consensus and cohesion in sociology and describe plans for future work on other fields.

This talk series continues in Spring 2006.