Information, Meaning, and Intellectual Organization in Networks of Inter-Human Communication

Introduction Due to the salience of citations in bibliometrics, there have been periodic calls for a theory of citations (e.g., Amsterdamska & Leydesdorff, 1989; Cozzens, 1989; Cronin, 1981, 1984, 1998; Garfield, 1979; Kaplan, 1965; Leydesdorff, 1998; Leydesdorff & Amsterdamska, 1990; Luukkonen, 1997; Nicolaisen, 2007; Woolgar, 1991; Wouters, 1998, 1999). Theories about citation tend to emphasize the relational aspect—that is, citation relations among authors and/or documents. Relations can also be aggregated into networks and the citation networks can be analyzed using social network analysis (e.g., Hummon & Doreian, 1989; Otte & Rousseau, 2002). However, neither meaning nor knowledge is purely relational. Meaning, rather, is provided positionally, not relationally. Unlike Shannon-type information—that is, the uncertainty in a probability distribution (Shannon, 1948, p. 10)—meaning can only be provided with reference to a system for which “the differences make a difference” at a place (MacKay, 1969; Bateson, 1973, p. 315). I shall argue that systems can be considered as sets of relations that are the results of first-order relations. However, the sets relate at the systems level not in terms of individual relations, but in terms of correlations. Because of potentially spurious correlations among two distributions of relations given a third one, uncertainty can also be reduced in the case of interactions among three (or more) sources of variation (Strand & Leydesdorff, 2013; cf. Garner & McGill, 1956). This communication at the systems level can be expressed as mutual information in the overlap among the sets—or with the opposite sign of reduction of uncertainty as mutual redundancy.