Time & Place:
Meetings will be held every Thursday 4:00-5:00pm in the Main Library LI 036, IUB and virtually in a 3-D online space. Read Accessing the Audio/Video Stream & Entering the Virtual Meeting Space. This way, you can attend remotely and people outside IU can participate. In addition, we plan to invite some of the authors of the discussed papers and system prototypes to join us remotely.

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

Participants:
Alice Robbin, Associate Professor Information Science, SLIS <arobbin@indiana.edu>
Amy H. Criss, Ph.D. student, Psychology <acriss@indiana.edu>
Benjamin Ashpole, CogSci major, COAS <bashpole@indiana.edu>
Chaomei Chen, Drexel University <Chaomei.Chen@cis.drexel.edu>
Diana Burley Gant, Assistant Professor Information Systems, Kelley School of Business <dbgant@indiana.edu>
Noriko Hara, Visiting Assistant Professor of Information Science, SLIS <nhara@indiana.edu>
Elin K. Jacob, Associate Professor Information Science, SLIS <ejacob@indiana.edu>
John Paolillo, Associate Professor Information Science, SLIS <paolillo@indiana.edu>
Kevin Boyack, Sandia National Laboratories <kboyack@sandia.gov>
Leonard John Old, Ph.D. student, SLIS <jold@indiana.edu>
Mark Steyvers, Postdoctoral Fellow, Psychology Department, Stanford University <msteyver@psych.stanford.edu>
McKim, Geoffrey,  Ph.D. student, SLIS  <geoff@TSC.com>
Ryan Scherle, Ph.D. student, CS <rscherle@cs.indiana.edu>
Tom Duffy, Chair of Education and Technology, School of Education <duffy@indiana.edu>
Travis Bauer, Ph.D. student, CS <trbauer@indiana.edu>
Xinye Wang, grad student, CS <xinywang@iago.ucs.indiana.edu>

To suggest additional readings or to join the group please send email to katy@indiana.edu or to the group alias katy_reading@indiana.edu.

Linton C. Freeman (2000) Visualizing Social Networks. Journal of Social Structure, 1 (1).

This paper documents the use of pictorial images in social network analysis. It shows that such images are critical both in helping investigators to understand network data and to communicate that understanding to others.

The paper reviews the long history of image use in the field. It begins with illustrations of the earliest hand-drawn images in which points were placed by using ad hoc rules. It examines the development of systematic procedures for locating points. It goes on to discuss how computers have been used to actually produce drawings of networks, both for printing and for display on computer screens. Finally, it illustrates some of the newest procedures for producing web-based pictures that allow viewers to interact with the network data and to explore their structural properties.

Barry Wellman (2000) Computer Networks as Social Networks. Science, Vol. 293, pp. 2031-2034.

Mark Granovetter (1973) The strength of weak ties. American Journal of Sociology. 81, 1287-1303.

Mark Granovetter (1983) The strength of weak ties. A Network Theory Revisited. Sociological Theory. 1, 201-233.

Noriko Hara (in press). Analysis of Computer-Mediated Communication Using Formal Concept Analysis as a Visualizing Methodology. Journal of Educational Computing Research.

L.C. Freeman and D.R. White (1993) Using Galois Lattices to Represent Network Data. In P.V. Marsden, ed. Sociological Methodology 1993. Oxford: Blackwell, 1993, 127-146.

Thomas Schweizer (1997) Embeddedness of Ethnographic Cases: A Social Networks Perspective. Current Anthropology 38, pp. 739-60.

As the world becomes more complex, the work of anthropology, both theoreticaland practical, becomes more demanding. Today, people at the local levelincreasingly are being drawn into larger circuits through economic linkages, demographic processes, social interactions, and flows of information that transcend local and national boundaries. Such global linkages and the newembeddedness they produce require more sophisticated approaches to ethnography. This paper proposes social network analysis as a valuable perspective to that end. The concept of embeddedness, which is central to the social networks perspective, is first introduced. Then follows network studies of two ethnographic cases, gift-giving among !Kung and ritual celebrations in a Javanese village, which illustrate the potential of social network analysis for investigating embeddedness. The paper concludes with substantive and methodological suggestions for the study of embeddedness.

Similarity & N-Grams

Dekang Lin (1998) An Information-Theoretic Definition of Similarity.

Provides a basis for a conceptual discussion of what constitutes similarity, and then shows some examples, including a at least one fairly specific one from information retrieval.  It think it would be a good paper to start a general discussion on the topic of similarity. (Travis Bauer)

M. Damashek. Gauging similarity with n-grams: Language independent categorization of text. Science, 267(5199):843--848, 1995.

Similarity

Krumhansl (1978) Concerning the applicability of geometric models to similarity data: the interrelationship between similarity and spatial density. Psychological Review, 85, 445-463.

Pruzansky, Tversky & Carroll (1982) Spatial versus tree representations of proximity data. Psychometrika, 47, 3-24.

Scaling

Young (1984) Scaling. Annual review of psychology, 35, 55-81.

Carroll (1976) Spatial, non-spatial, and hybrid models for scaling. Psychometrika, 41, 439-463

MDS

Zinnes & McKay (1983). Probabilistic multidimensional scaling: Complete and incomplete data. Psychometrika 48, 27-48.

Roger N. Shepard. Multidimensional scaling, tree-fitting, and clustering. Science, 210:390--397, 1980.

Nonlinear MDS using Isomap

Balasubramanian, M., Schwartz, E. L., Tenenbaum, J. B., de Silva, V., Langford, J. C. (2002). The Isomap Algorithm and Topological Stability. Science 295 (5552) 7a-7.
While MDS is limited to a small data sets, the Isomap model is capable of placing thousands of points in a space. The new sparse version of Isomap can potentially scale up to quite large datasets.

Joshua B. Tenenbaum, Vin de Silva, and John C. Langford (2000) A Global Geometric Framework for Nonlinear Dimensionality Reduction.  Science 290 (5500) 2319-2323.

Isomap model web page: http://isomap.stanford.edu/

Locally Linear Embedding - An alternative approach to Isomap

Sam T. Roweis and Lawrence K. Saul (2000) Nonlinear Dimensionality Reduction by Locally Linear Embedding. Science 290 (5500) 2323-2326.

Bernd Fritzke, A growing neural gas network learns topologies, NIPS 1994 Denver.

B. Fritzke, Growing self-organizing networks - history, status quo, and perspectives. In Kohonen Maps,  Proceedings of WSOM-99, eds. E. Oja et. al.,  Elsevier 1999, (to appear)

C.T. Zahn. Graph-Theoretical Methods for Detecting and Describing Gestalt Clusters. IEEE Transactions on Computers, 20:68--86, 1971.

J. Paolillo. Language variation on Internet Relay Chat: A social network approach. Journal of Sociolinguistics 5/2, 2001:180-213.

Social Network Visualization by Vladimir Batagelj
http://vlado.fmf.uni-lj.si/
Pajek 0.72 available at http://vlado.fmf.uni-lj.si/pub/networks/pajek/

Fast and Noise Tolerant Clustering in VxInsight
http://www.cs.sandia.gov/projects/VxInsight.html

Complex Human Networks  Reading Group (CoHN) (2000) tries to explore the methods used in understanding structural and behavioral properties of  large complex interactive networks
Markovia Reading Group (1999) aims to explore ways of modeling, comparing, discriminating, and understanding time series.

The Erdös Number Project
Albert-László Barabási's Self Organized Networks web site
Internet Topology Project by Ramesh Govindan et al., University of Michigan
Graphic Imaging Source for Social Network Analysis by Lin Freeman
Computer Programs for Social Network Analysis by the International Network for Social Network Analysis
Social Network Analysis Instructional Web Site by Steve Borgatti
International Network for Social Network Analysis by Stephen P. Borgatti & Cathleen McGrath
Social Network Analysis site by Tom Snijders
Evolving Networks research by Holger Ebel

Complex Interactive Networks Workshop at Santa Fe Institute, August 2000
Networks and Complexity in Social System course by D. J. Watts
Social Networks course by James Moody

Econometrics Toolbox by James P. LeSage

Social Networks Journal

Software:
UCI-NET version 5.4 available for $40 from Analytic Technologies (www.analytictech.com)
UCINET 4, for DOS is free and can be downloaded at http://www.analytictech.com/free_software.htm
STRUCTURE by Ron Burt is free and has much the same functionality as UCINET ( http://www.columbia.edu/cu/css/download.htm) the structure manual is very substantive.
KRACKPLOT (http://www.contrib.andrew.cmu.edu/~krack/)
SPAN (Sas Programs for Analyzing Networks) by James Moody is free (http://www.soc.sbs.ohio-state.edu/jwm/)
PAJEK - analyzes large networks and is arguably the best drawing program on the market (http://vlado.fmf.uni-lj.si/pub/networks/pajek/default.htm)

HomeFacultyKaty BörnerReading Group
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Last modified: 09/05/2002