Dear Joseph,
I looked with great interest at this paper, skeptical, as Loet could have imagined. I will formulate my reaction in terms of two propositions, hoping that useful answers may emerge: 1. To what extent are all the elements in your diagrams static elements of a classification, without intrinsic dynamic (that is energetic) properties and capacity for change? One can map these diagrams for different moments in time and then animate a best fit along the time axis. Since 2004 there is an algorithm for multidimensional scaling along the time axis available that was incorporated in visone (http://www.leydesdorff.net/visone). One thus catches the historical dynamics. The evolutionary dynamics are more difficult to capture. These are instantiations. At the end of the paper I refer to my work on anticipatory systems for the algorithms needed for capturing the dynamics of meaning. Hitherto, we have not managed to capture these in relation to language. See for a capturing in terms of representations at http://www.leydesdorff.net/netsci/index.htm . 2. What aspects of meaning are not captured in the vector space you generate? These are proxies in language. Symbolic generalization, for example, is not captured in this way. It may be underlying, but that does not have to be the case. In classes, for example, I sometimes ask students to make representations of scholarly discourse, political discourse, and newspapers about a specific issue. Then, one can observe the different frames induced by different symbolically generalized media. I took the freedom to resend this back to the FIS network. Best wishes for a Happy New Year, Loet Best wishes for a healthy and productive New Year, in which our views will both converge and diverge! Joseph ----- Original Message ----- From: Loet Leydesdorff <mailto:[email protected]> To: [email protected] Sent: Friday, December 30, 2011 9:20 AM Subject: Re: [Fis] Common Ground - Discussion of Information ScienceEducation Visualization and Analysis of Frames in Collections of Messages: <http://arxiv.org/ftp/arxiv/papers/1112/1112.6286.pdf> Content Analysis and the Measurement of Meaning Esther Vlieger & Loet Leydesdorff A step-to-step introduction is provided on how to generate a semantic map from a collection of messages (full texts, paragraphs or statements) using freely available software and/or SPSS for the relevant statistics and the visualization. The techniques are discussed in the various theoretical contexts of (i) linguistics (e.g., Latent Semantic Analysis), (ii) sociocybernetics and social systems theory (e.g., the communication of meaning), and (iii) communication studies (e.g., framing and agenda-setting). We distinguish between the communication of information in the network space (social network analysis) and the communication of meaning in the vector space. The vector space can be considered a generated as an architecture by the network of relations in the network space; words are then not only related, but also positioned. These positions are expected rather than observed and therefore one can communicate meaning. Knowledge can be generated when these meanings can recursively be communicated and therefore also further codified. Forthcoming in: Manuel Mora, Ovsei Gelman, Annette Steenkamp, and Maresh S. Raisinghani (Eds.), Research Methodologies, Innovations and Philosophies in Systems Engineering and Information Systems, Hershey PA: Information Science Reference, 2012, pp. 322-340, doi: 10.4018/978-1-4666-0179-6.ch16. Loet Leydesdorff Professor, University of Amsterdam Amsterdam School of Communications Research (ASCoR), Kloveniersburgwal 48, 1012 CX Amsterdam. Tel.: +31-20- 525 6598; fax: +31-842239111 [email protected] ; http://www.leydesdorff.net/; http://scholar.google.com/citations?user=ych9gNYAAAAJ <http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en> &hl=en _____ _______________________________________________ fis mailing list [email protected] https://webmail.unizar.es/cgi-bin/mailman/listinfo/fis
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