Introduction to Complexity
Complexity theory is a major interdisciplinary paradigm which unifies natural
and social sciences through a combination of quantitative and qualitative
methods applied at various phases of the research, from observations and
data analysis to modeling, simulation, and interpretation of complex
phenomena (Anderson, 1972; Ross and Arkin, 2009). In this framework,
cognitive and nonlinear stochastic models and effective representation
methods such as complex networks and fractal geometry, represent a part of
the standard toolbox. In fact, in complexity theory, phenomena emerge
dynamically from hierarchical, multi-modular systems, produced by bundles of
possibly stochastic interactions and causalities rather than from
correlative determinism.
As far as language and linguistic analysis are concerned, complexity itself
can be understood from at least two different perspectives. On the one hand,
there is ‘constitutional complexity’, or ‘bit
complexity’, that is, complexity due to inventories of functional
units or structural features, such as phonemes, morphemes, and lexical
stems. On the other hand, there is ‘(socio-)interactional
complexity’, or, in other words, ‘communal complexity’,
involving intricate modules of units and features, or networks of
interactive individuals and aggregates. These different aspects all find
their natural description in the multiplex paradigm, that
is, through a model system composed of a set of interacting, overlapping
networks. The unification of the two aforementioned dimensions of complexity
represents a major challenge and is a focus point of this book.
For more than a decade, a growing interdisciplinary community has applied the
tools of complex systems theory and statistical mechanics to the study of
problems that traditionally belong to the field of linguistics. Nowadays,
language dynamics represents a relevant branch of complexity theory. The
modeling of language dynamics has mainly addressed three fundamental
dimensions of language complexity.
(i) Language spread and competition (the dynamics of language
use in multilingual communities).
(ii) Language evolution (how the structure of language
evolves).
(iii) Language cognition (the way the human brain processes
linguistic knowledge).
While these three dimensions of language complexity closely interact with
each other and should all be taken into account for an exhaustive
description of language complexity, it is useful, for clarity, to consider
them as separate aspects. In the present book, we mainly address the first
two dimensions, discussing language spread and competition models and
considering language evolution models. However, we will also use
socio-cognitive models of linguistic and cultural change.