Social complexity

[3] Social complexity is a basis for the connection of the phenomena reported in microsociology and macrosociology, and thus provides an intellectual middle-range for sociologists to formulate and develop hypotheses.

From the late 1970s until the early 1990s, sociological investigation concerned the properties of systems in which the strong correlation of sub-parts leads to the observation of autopoetic, self-organizing, dynamical, turbulent, and chaotic behaviours that arise from mathematical complexity, such as the work of Niklas Luhmann.

Within this body of work, connections also are drawn to yet other theoretical traditions, including constructivist epistemology and the philosophical positions of phenomenology, postmodernism and critical realism.

Methodologically, social complexity is theory-neutral, meaning that it accommodates both local and global approaches to sociological research.

More recently, highly sophisticated quantitative research methodologies are being developed and used in sociology at both local and global levels of analysis.

New computational methods of localized social network analysis are coming out of the work of Duncan Watts, Albert-László Barabási, Nicholas A. Christakis, Kathleen Carley and others.

The development of computational sociology involves such scholars as Nigel Gilbert, Klaus G. Troitzsch, Joshua M. Epstein, and others.

Sociocybernetics integrates sociology with second-order cybernetics and the work of Niklas Luhmann, along with the latest advances in complexity science.

One common criticism often cited regarding the usefulness of complexity science in sociology is the difficulty of obtaining adequate data.

From childhood friendships and teen pregnancy[2] to criminology[35] and counter-terrorism,[36] theories of social complexity are being applied in almost all areas of sociological research.