# The mechanisms of self-organised criticality in social processes of knowledge creation

## TL;DR

This paper investigates the emergence of self-organised criticality in social knowledge creation processes, analyzing empirical data from Q&A platforms and theoretical models to understand the dynamics and factors influencing large-scale collaborative events.

## Contribution

It introduces a combined empirical and theoretical approach to study social avalanches in knowledge creation, highlighting the role of social dynamics and cognitive contents in scaling behaviors.

## Key findings

- Long-range correlations driven by new user arrivals
- Cognitive contents influence avalanche structure and exponents
- Increased activity correlates with higher innovation fluctuations

## Abstract

In the online social dynamics, a robust scaling behaviour appears as a key feature of many collaborative efforts that lead to the new social value. The underlying empirical data thus offer a unique opportunity to study the origin of self-organised criticality in social systems. In contrast to physical systems in the laboratory, various human attributes of the actors play an essential role in the process along with the contents (cognitive, emotional) of the communicated artefacts. As a prototypal example, we consider the social endeavour of knowledge creation via Questions\ \& Answers (Q\&A). Using a large empirical dataset from one of such Q\&A sites and theoretical modelling, we examine the temporal correlations at all scales and the role of cognitive contents to the avalanches of the knowledge creation process. Our analysis shows that the long-range correlations and the event clustering are primarily determined by the universal social dynamics, providing the external driving of the system by the arrival of new users. While the involved cognitive contents (systematically annotated in the data and observed in the model) are crucial for a fine structure of the developing knowledge networks, they only affect the values of the scaling exponents and the geometry of large avalanches and shape the multifractal spectrum. Furthermore, we find that the level of the activity of the communities that share the knowledge correlates with the fluctuations of the innovation rate, implying that the increase of innovation may serve as the active principle of self-organisation. To identify relevant parameters and unravel the role of the network evolution underlying the process in the social system under consideration, we compare the social avalanches to the avalanche sequences occurring in the field-driven physical model of disordered solids.