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Dear Courtney and colleagues,
At my website, one can find the following software which may be relevant to this issue:
Ti.Exe (at http://www.leydesdorff.net/software/ti ) uses as input a set of lines (e.g., titles; < 1000 characters) and generates the word/document occurrence matrix in the Pajek format. Additionally, a file "cosine.dat" is produced which normalizes the word occurrences using the cosine. Alternatively, one can import the output in Pajek or UCINet and generate the 1-mode affiliations matrices.
FullText.Exe (at http://ww.leydesdorff.net/software/fulltext ) which uses an unlimited number of ASCII texts as cases and equally produces a word/document occurrence matrix.
Both programs have a limit of 1024 words as variables. One can first run a word frequency analysis for determining the thresholds. Programs for that are also available. For example, the term-frequency/inversed document frequency and the contribution of each word to the chi-square can be provided.
I use these programs heavily in my research and education, but further feedback for improving them is of course appreciated. For example: Loet Leydesdorff & Iina Hellsten, Metaphors and Diaphors in Science Communication: Mapping the Case of ‘Stem-Cell Research’, Science Communication 27(1), 2005, 64-99. <pdf-version>
***** To join INSNA, visit http://www.insna.org ***** Thanks again to all of those who shared resources :-)
The following is a summary of the responses I received to my request for citations for studies combining content analysis with social network analysis:
AutoMap - Jana Diesner
Discourse Network Analyzer - Philip Leifeld
Crawdad - Steve Corman, ASU
John Mohr, University of California Santa Barbara
Jana Diesner, Carnegie Mellon University
Philip Leifeld, Max Planck Institute for Research on Collective Goods
Ron Rice, University of California Santa Barbara
Kathleen Carley, Carnegie Mellon University
Filippo Menczer, Indiana University Bloomington
Michael Stefanone, University of Buffalo
Cynthia Stohl, University of California Santa Barbara
Marya L. Doerfel, Rutgers University
Loet Leydesdorff, Amsterdam School of Communication Research
Ackland, R., Gibson, R., Lusoli, W. and S. Ward (2010), "Engaging with the public? Assessing the online presence and communication practices of the nanotechnology industry," forthcoming in Social Science Computer Review, accepted 19 June 2009. Pre-print: http://voson.anu.edu.au/papers/Nanotech_SSCORE_2010.pdf
Aral and Van Alstyne (2009) "Networks Information and Brokerage: The Diversity-Bandwidth Tradeoff"
Available at SSRN: http://ssrn.com/abstract=958158
Blaschke, S., Schoeneborn, D., and Seidl, D. (2009). Organizations as Networks of Communications: A Methodological Proposal. Working Paper No. 102, University of Zurich. http://ssrn.com/abstract=1512471
Burt (2008) "Information and Structural Holes: Comment on Reagans and Zuckerman." Industrial and Corporate
Change, 17(5), pp. 953-69.
Available at: http://icc.oxfordjournals.org/cgi/content/full/dtn033v1
Corman, S. R., Kuhn, T., McPhee, R. D., & Dooley, K. J. (2002). Studying
Complex Discursive Systems: Centering Resonance Analysis of Communication.
Human Communication Research, 28(2), 157-206.
Chow-White, Peter A. (2006) “Race, gender and sex on the net: semantic networks of selling and storytelling sex tourism.” Media, Culture & Society. 28(6): 883-905.http://mcs.sagepub.com/cgi/reprint/28/6/883
Diesner, J., & Carley, K. M. (2005). Revealing Social Structure from Texts:
Meta-Matrix Text Analysis as a novel method for Network Text Analysis. In V.
K. Narayanan & D. J. Armstrong (Eds.), Causal Mapping for Information
Systems and Technology Research: Approaches, Advances, and Illustrations
(pp. 81-108). Harrisburg, PA: Idea Group Publishing.
Diesner, J., & Carley, K. M. (2008). Conditional Random Fields for Entity
Extraction and Ontological Text Coding. Journal of Computational and
Mathematical Organization Theory, 14, 248 - 262.
Doerfel, M.L. & G.A. Barnett, A Comparison of the Semantic and Affiliation Networks of the International Communication Association. Human Communication Research, 25 (4), 589-603, 1999.
Frank Janning, Philip Leifeld, Thomas Malang and Volker Schneider (2009): Diskursnetzwerkanalyse. Überlegungen zur Theoriebildung und Methodik. In: Volker Schneider, Frank Janning, Philip Leifeld and Thomas Malang (eds.): Politiknetzwerke - Modelle, Anwendungen und Visualisierungen. Pages 59-92. Wiesbaden: VS Verlag für Sozialwissenschaften.
Franzosi, Roberto. 1989. "From Words to Numbers: A Generalized and Linguistics-Based Coding Procedure for Collecting Textual Data." Sociological Methodology 19: 263-298.
Franzosi, Roberto. 1990. "Computer-Assisted Coding of Textual Data: An Application to Semantic Grammars." Sociological Methods and Research 19(2): 225-257.
Gloor, P., & Zhao, Y. (2006, July 2006). Analyzing actors and their
discussion topics by semantic social network analysis. Paper presented at
the 10th IEEE International Conference on Information Visualisation London.
Gruzd, A. A. (April 1, 2009). Automated Discovery of Social Networks in Online Learning Communities. Doctoral dissertation, University of Illinois at Urbana-Champaign, Urbana, IL. Available at http://anatoliygruzd.com/pub/gruzd_anatoliy.pdf
Gruzd, A. (2009). Studying Collaborative Learning using Name Networks. Journal of Education for Library and Information Science (JELIS) 50(4): 243-253. Available at http://anatoliygruzd.com/pub/gruzd_2009_jelis_name_networks.pdf
Gruzd,A. (2009). Automated Discovery of Emerging Online Communities Among Blog Readers: A Case Study of a Canadian Real Estate Blog. Proceedings of the Internet Research 10.0 Conference, October 7-11, 2009, Milwaukee, WI, USA. Available at http://anatoliygruzd.com/pub/gruzd_aoir_network_discovery.pdf
Jang, H. & G.A. Barnett, Cultural Differences in Organizational Communication: A Semantic Network Analysis. Bulletin de Methodologie Sociologique, 44, 31-59, 1994.
Johnson and Krempel (Vol 5 No. 1) "Network Visualization: The Bush Team in Reuters News Tickers 9/11/01-11/15/01.Kapucu, Naim, Maria-Elena Augustin and Vener Garayev. (2009).
*Interstate Partnerships in Emergency Management: Emergency
Management Assistance Compact (EMAC) in Response to Catastrophic
Disasters,* Public Administration Review. Volume 69 (2): 297-313.
Leifeld, Philip, and Sebastian Haunss (2010), A Comparison between Political Claims Analysis and Discourse Network Analysis: The Case of Software Patents in the European Union, Preprints of the Max Planck Institute for Research on Collective Goods Bonn 2010/21, Bonn: Max Planck Institute for Research on Collective Goods [available at http://www.coll.mpg.de/pdf_dat/2010_21online.pdf].
"No Guru, No Method, No Teacher: Self-classification and Self-modelling of E-Learning Communities" http://www.springerlink.com/content/16j05454w8682687/fulltext.pdf
Oliver, A.L. and M. Ebers. 1998. Networking Network Studies - An Analysis of Conceptual Configurations in the Study of Inter-Organizational Relations. Organization Studies, 19, 4:549-583
Oliver, A.L and K. Montgomery. 2005. Toward the construction of a profession’s boundaries: Creating a networking agenda. Human Relations, 58:1167-1184.
Oliver A.L. and K. Montgomery. 2008. Using Field Configuring Events for Sense Making: A Cognitive Network Approach, Journal of Management Studies, 45:6, 1147-1167.
Smith, A., & Humphreys, M. (2006). Evaluation of unsupervised semantic
mapping of natural language with Leximancer concept mapping. Behavior
Research Methods, 38(2), 262-279.
Brian Ulicny, Mieczyslaw M. Kokar, Christopher J. Matheus, "Metrics
For Monitoring A Social-Political Blogosphere: A Malaysian Case
Study," IEEE Internet Computing, vol. 14, no. 2, pp. 34-44, Mar./Apr.
2010, Special Issue on Social Computing in the Blogosphere.
Van Atteveldt, W. (2008). Semantic network analysis: Techniques forWhite, K.R. & Dandi, R. (2009). Intrasectoral Variation in Mission and Values: The Case of Catholic Health Care Systems. Health Care Management Review 34(1): 68-79
extracting, representing, and querying media content. Charleston, SC:
Yates, J. and Orlikowski, W. J. (1992). Genres of Organizational Communica- tion: A Structural Approach to Studying Communication and Media. Academy of Management Review, 17(2):299–326.
Zelenko, D., Aone, C., & Richardella, A. (2003). Kernel methods for relation
extraction. The Journal of Machine Learning Research, 3, 1083-1106.
http://www.mande.co.uk/ghana/Analysis of narrative reports26July2007Revised.doc
Enjoying the strength of weak ties,
S. Courtney Walton
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Department of Communication
4309 Social Sciences & Media Studies Bldg
University of California, Santa Barbara
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