This article explores the emergence of knowledge from scientific discoveries and their effects on the structure of scientific communication. Network analysis is applied to understand this emergence institutionally as changes in the journals; semantically, as changes in the codification of meaning in terms of words; and cognitively as the new knowledge becomes the emergent foundation of further developments. The discovery of fullerenes in 1985 is analyzed as the scientific discovery that triggered a process which led to research in nanotubes. 1.

Discursive knowledge emerges as codification in flows of communication. The flows of communication are constrained and enabled by networks of communications as their historical manifestations at each moment of time. New publications modify the existing networks by changing the distributions of attributes and relations in document sets, while the networks are self-referentially updated along trajectories. Codification operates reflexively: the network structures are reconstructed from the perspective of hindsight. Codification along different axes differentiates discursive knowledge into specialties. These intellectual control structures are constructed bottom-up, but feed top-down back upon the production of new knowledge. However, the forward dynamics of diffusion in the development of the communication networks along trajectories differs from the feedback mechanisms of control. Analysis of the development of scientific communication in terms of evolving scientific literatures provides us with a model which makes these evolutionary processes amenable to measurement.

Using aggregated journal-journal citation networks, the measurement of anticipation in empirical systems is examined in two cases of interdisciplinary developments during the period 1995-2005: (i) the development of nanotechnology in the natural sciences and (ii) the development of communication studies as an interdiscipline between social psychology and political science. The results are compared with a case of stable development: the citation networks of core journals in chemistry. The textual networks are intellectually organized by networks of expectations in the knowledge base at the specialty (that is, above-journal) level. This “structuration ” of structural components in the observable networks can be measured as configurational information. The latter can be compared with the Shannon-type information generated in the interactions among structural components: the difference between these two measures provides us with a redundancy generated by the specification of a model in the knowledge base of the system. The knowledge base incurs to variable extents on the knowledge infrastructures provided by the networks of exchange relations.

the social sciences