Can "Hot Spots" in the Sciences Be Mapped Using the Dynamics of Aggregated Journal-Journal Citation Relations?

TL;DR

This study uses entropy-based methods and network analysis on journal citation data from 2011-2013 to identify potential scientific 'hot spots' and analyze citation dynamics, revealing significant unexpected developments and the impact of PLoS ONE.

Contribution

It introduces a novel combination of entropy statistics and network analysis to map and detect emerging 'hot spots' in scientific citation networks.

Findings

Identified 78 clusters with potential 'hot spots' in citation networks.

Flagged 74 journals with discontinuous citation changes.

Detected PLoS ONE's influence on communication dynamics.

Abstract

Using three years of the Journal Citation Reports (2011, 2012, and 2013), indicators of transitions in 2012 (between 2011 and 2013) are studied using methodologies based on entropy statistics. Changes can be indicated at the level of journals using the margin totals of entropy production along the row or column vectors, but also at the level of links among journals by importing the transition matrices into network analysis and visualization programs (and using community-finding algorithms). Seventy-four journals are flagged in terms of discontinuous changes in their citations; but 3,114 journals are involved in "hot" links. Most of these links are embedded in a main component; 78 clusters (containing 172 journals) are flagged as potential "hot spots" emerging at the network level. An additional finding is that PLoS ONE introduced a new communication dynamics into the database. The limitations of the methodology are elaborated using an example. The results of the study indicate where developments in the citation dynamics can be considered as significantly unexpected. This can be used as heuristic information; but what a "hot spot" in terms of the entropy statistics of aggregated citation relations means substantively can be expected to vary from case to case.