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Here are the summary responses for my request on info regarding structural
linguistics and network analysis that I posted about three weeks back.
Thanks to all the contributors. A special thanks to Joe Labianca at Emory.
Dr. Steve Corman and Dr. Kevin Dooley have developed a software application
"Crawdad" that is based on Centering Resonance Analysis. I have found that
tool to be very useful. http://www.crawdadtech.com/
From: Christina Prell <[log in to unmask]>
The work of Law and Callon, especially their early work (from the mid
80s) might be useful. They attempt to apply semiotics to the study of
technology and science, in particular articles, and they use an approach
similar to social ntwork analysis.
From: "Jana Diesner" <[log in to unmask]>
Carley, K.M., Diesner, J., Reminga, J., Tsvetovat, M. (2004). An Integrated
Approach to the Collection and Analysis of Network Data. In Proc of the
North American Association for Computational Social and Organizational
Science (NAACSOS) 2004 Conference, Pittsburgh, PA. Diesner, J., & Carley,
K.M. (2004). Using Network Text Analysis to Detect the Organizational
Structure of Covert Networks. In Proc of the North American Association for
Computational Social and Organizational Science (NAACSOS) 2004 Conference,
Pittsburgh, PA. URL:
Diesner, J., & Carley, K.M. (2004). Using Network Text Analysis to Detect
the Organizational Structure of Covert Networks. In Proc of the North
American Association for Computational Social and Organizational Science
(NAACSOS) 2004 Conference, Pittsburgh, PA. URL:
Diesner, J., & Carley, K.M. (2004 - in print). Revealing Social Structure
from Texts: Meta-Matrix Text Analysis as a novel method for Network Text
Analysis. In V.K Naraynan, & D.J. Armstrong (Eds.), Causal Mapping for
Information Systems and Technology Research: Approaches, Advances, and
Illustrations. Harrisburg, PA: Idea Group Publishing, pp.
Kathleen M. Carley, 1997, "Network Text Analysis: The Network Position of
Concepts." Chapter 4 in C. Roberts (Ed.), Text Analysis for the Social
Sciences: Methods for Drawing Statistical Inferences from Texts and
Transcripts. Hillsdale, NJ: Lawrence Erlbaum Associates. pp. 79-100.
Kathleen M. Carley, 1997, "Extracting Team Mental Models Through Textual
Journal of Organizational Behavior, 18: 533-538.
Kathleen Carley, 1994. "Extracting Culture through Textual Analysis."
David Kaufer & Kathleen Carley, 1993, "Condensation Symbols: Their Variety
and Rhetorical Function in Political Discourse." Philosophy and Rhetoric ,
Kathleen Carley & Michael Palmquist, 1992, "Extracting, Representing and
Analyzing Mental Models."
Social Forces , 70(3): 601-636.
From: Maryann Durland <[log in to unmask]>
another resource might be a recent post on biblometric data: here is the
last part of the post:
I hope that the software is of use to someone. It is freely available at
_http://www.sitkis.com/_ (http://www.sitkis.com/) or
_http://www.hut.fi/~hschildt/sitkis_ (http://www.hut.fi/~hschildt/sitkis) .
From: Steve Abrams <[log in to unmask]>
You might want to investigate the literature of "formal concept analysis"
(eg http://www.upriss.org.uk/fca/fca.html) which, at its most basic, uses a
Galois lattice representation (see Wasserman and Faust) of binary two-mode
network data (eg rows=documents, columns=words/phrases, cell values = 1 if
the word/phrase is found in the document; you can also make the rows=
chapters, paragraphs, or even sentences depending on the granularity).
Monge and Contractor also write about p* modeling of semantic texts ... Ch.
5 as I recall ...
I am using both of these approaches in my dissertation research, so I hope
you'll post a summary of responses you get ...
From: "Prabir G. Dastidar" <[log in to unmask]>
you can see the CATPAC (categorical package) web site. This is a software
(I also use this), uses neural network technology to analyse texts and
gives out a matrix (normalised)of interactions between the words, along
with Multidimensional Scaling map. You can use this matrix for doing
network analysis as well. If you feel like I can send you some references
on similar topics.
Penn State University
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