Andrzej Pekalski networks of scientific interests with internal degrees of freedom through self-citation analysis

TL;DR

This paper analyzes Andrzej Pekalski's self-citation network over four decades to reveal insights into scientific interest evolution, community formation, and the complex dynamics driven by internal degrees of freedom and external shocks.

Contribution

It introduces a novel analysis of Pekalski's self-citation patterns to understand scientific community dynamics and network formation through complex systems theory.

Findings

Pekalski's self-citation network shows distinct clusters.

Network evolution involves rare, drastic events akin to phase transitions.

Internal degrees of freedom influence network resilience and interest shifts.

Abstract

Old and recent theoretical works by Andrzej Pekalski (APE) are recalled as possible sources of interest for describing network formation and clustering in complex (scientific) communities, through self-organisation and percolation processes. Emphasis is placed on APE self-citation network over four decades. The method is that used for detecting scientists field mobility by focusing on author's self-citation, co-authorships and article topics networks as in [1,2]. It is shown that APE's self-citation patterns reveal important information on APE interest for research topics over time as well as APE engagement on different scientific topics and in different networks of collaboration. Its interesting complexity results from "degrees of freedom" and external fields leading to so called internal shock resistance. It is found that APE network of scientific interests belongs to independent clusters and occurs through rare or drastic events as in irreversible "preferential attachment processes", similar to those found in usual mechanics and thermodynamics phase transitions.