Are Word-Adjacency Networks Networks?

  • Katharina Anna Zweig
Part of the Understanding Complex Systems book series (UCS)


This article discusses the question of whether word-adjacency relationships are well-represented by a complex network. The main hypothesis of this work is that network representations are best suited to analyze indirect effects. For an indirect effect to occur in a network, a network process needs to exist that uses the network to exert an indirect effect, e.g., the spreading of a virus in a social network after a small group of persons were infected. Given any sequence of words, it can be represented by a so-called word-adjacency network by representing each word by a node and by connecting two nodes if the corresponding words are directly adjacent or at least close to each other in this sequence. It can be easily seen that the result of a speech production process gives rise to a word-adjacency network but it is unlikely that speech production uses an underlying word-adjacency network—at least not in any easily describable way. Thus, the results of clustering algorithms, centrality index values, and the results of other distance-based measures that quantify indirect effects cannot be interpreted with respect to speech production.


Short Path Network Analysis Complex Network Social Network Analysis Betweenness Centrality 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Graph Theory and Complex Network Analysis, Department of Computer ScienceTU KaiserslauternKaiserslauternGermany

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