the communication of meaning, information, and discursive knowledge; preprint versions

[Loet Leydesdorff]

Advances in Science Visualization:
<http://arxiv.org/ftp/arxiv/papers/1206/1206.3746.pdf> 
Social Networks, Semantic Maps, and Discursive Knowledge

Positional and relational perspectives on network data have led to two
different research traditions in textual analysis and social network
analysis, respectively. Latent Semantic Analysis (LSA) focuses on the latent
dimensions in textual data; social network analysis (SNA) on the observable
networks. The two coupled topographies of information-processing in the
network space and meaning-processing in the vector space operate with
different (nonlinear) dynamics. The historical dynamics of information
processing in observable networks organizes the system into instantiations;
the systems dynamics, however, can be considered as self-organizing in terms
of fluxes of communication along the various dimensions that operate with
different codes. The development over time adds evolutionary differentiation
to the historical integration; a richer structure can process more
complexity.

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Statistics for the Dynamic Analysis of Scientometric Data:
<http://arxiv.org/ftp/arxiv/papers/1206/1206.3747.pdf> 
The evolution of the sciences in terms of trajectories and regimes


The gap in statistics between multi-variate and time-series analysis can be
bridged by using entropy statistics and recent developments in
multi-dimensional scaling. For explaining the evolution of the sciences as
non-linear dynamics, the configurations among variables can be important in
addition to the statistics of individual variables and trend lines.
Animations enable us to combine multiple perspectives (based on
configurations of variables) and to visualize path-dependencies in terms of
trajectories and regimes. Path-dependent transitions and systems formation
can be tested using entropy statistics.

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The Communication of Meaning and Information,
<http://semioticon.com/sio/courses/the-communication-of-meaning-and-informat
ion-and-%E2%80%A8the-structuration-of-expectations-as-discursive-knowledge/>

and the Structuration of Expectations as Discursive Knowledge


 

In addition to many great discoveries, Galileo changed the philosophy of
science of his time by considering the Book of Nature not as a Revelation,
but as a text open to debate. He presented his arguments discursively in
Dialogo (1632) and Discorsi (1638). The older form of a disputatio which he
had used in earlier work (e.g., Disputatio de coelo, 1616) and which was
used also by his adversaries, was here abandoned in favor of open dialogue
as the prime mode of generating, validating, and reproducing knowledge
(Biagioli, 2003). Discursive knowledge-that is proceeding to a conclusion
through reasoning-is shaped in communication among reflexive participants in
the exchange (Husserl, 1929, 1935/6). The shaping of written knowledge in
scientific literature as we know it today followed thereupon as an
achievement of mainly the 18th century (Bazerman, 1988). 

 
<http://semioticon.com/sio/files/downloads/2012/06/Introduction_SIO_Leydesdo
rff.pdf> >> more >>

 

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** apologies for crosspostings.

 

Loet Leydesdorff 

University of Amsterdam
Amsterdam School of Communications Research (ASCoR)
Kloveniersburgwal 48, 1012 CX Amsterdam.
Tel. +31-20-525 6598; fax: +31-842239111

 <mailto:loet at leydesdorff.net> loet at leydesdorff.net ;
<http://www.leydesdorff.net/> http://www.leydesdorff.net/ 
Visiting Professor,  <http://www.istic.ac.cn/Eng/brief_en.html> ISTIC,
Beijing; Honorary Fellow,  <http://www.sussex.ac.uk/spru/> SPRU, University
of Sussex;  <http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en>
http://scholar.google.com/citations?user=ych9gNYAAAAJ&hl=en  



 

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