Scientometrics and Communication Theory: Towards Theoretically Informed Indicators

TL;DR

This paper proposes a network-based, theoretically informed approach to scientometrics, emphasizing communication dynamics and latent structures in citation networks to improve understanding of scientific communication.

Contribution

It introduces a new perspective that considers communication networks and their latent structures, extending traditional citation analysis with an evolutionary and network-based framework.

Findings

Identified non-homogeneous subdynamics in citation networks

Demonstrated the application using journal-journal citation data in STS

Discussed policy implications of network-based scientometrics

Abstract

A theory of citations should not consider cited and/or citing agents as its sole subject of study. One is able to study also the dynamics in the networks of communications. While communicating agents (e.g., authors, laboratories, journals) can be made comparable in terms of their publication and citation counts, one would expect the communication networks not to be homogeneous. The latent structures of the network indicate different codifications that span a space of possible 'translations'. The various subdynamics can be hypothesized from an evolutionary perspective. Using the network of aggregated journal-journal citations in Science & Technology Studies as an empirical case, the operation of such subdynamics can be demonstrated. Policy implications and the consequences for a theory-driven type of scientometrics will be elaborated.