Tracing the Development of the Virtual Particle Concept Using Semantic Change Detection

TL;DR

This study proposes using the intriguing case of virtual particles to discuss the efficacy of Semantic Change Detection (SCD) based on contextualized word embeddings from a domain-adapted BERT model in studying specific scientific concepts.

Abstract

Virtual particles are peculiar objects. They figure prominently in much of theoretical and experimental research in elementary particle physics. But exactly what they are is far from obvious. In particular, to what extent they should be considered "real" remains a matter of controversy in philosophy of science. Also their origin and development has only recently come into focus of scholarship in the history of science. In this study, we propose using the intriguing case of virtual particles to discuss the efficacy of Semantic Change Detection (SCD) based on contextualized word embeddings from a domain-adapted BERT model in studying specific scientific concepts. We find that the SCD metrics align well with qualitative research insights in the history and philosophy of science, as well as with the results obtained from Dependency Parsing to determine the frequency and connotations of the term "virtual." Still, the metrics of SCD provide additional insights over and above the qualitative research and the Dependency Parsing. Among other things, the metrics suggest that the concept of the virtual particle became more stable after 1950 but at the same time also more polysemous.

Figures (7)

• Figure 1: Overview of the Physical Review corpus: The figure displays the total number of published articles per year containing "virtual" for the entire corpus (on the left) and their proportion (rolling mean over 3 years) per journal (on the right). For clarity, the proportions in PR - Letters and RMP are not shown.
• Figure 2: Shifts in dominant meaning for "virtual", using PRT (left) and JSD for K-Means and AP-clustering (right) in the entire PR-corpus and over the entire investigation period.
• Figure 3: Changing degree of polysemy for "virtual", using AID (left) and normalized Shannon-Entropy for K-Means and AP-clustering (right) in the entire PR-corpus and over the entire investigation period.
• Figure 4: Number of published articles per year for each journal in the PR-corpus. The first dashed line indicates the transition from Series II to PR A - D, while the second dashed line marks a subsequent disciplinary differentiation around 2010.
• Figure 5: Shifts in dominant meaning in discipline-specific PR-journals for "virtual", using PRT (left) and JSD for K-Means clustering (right). For clarity, the rolling mean over 3 years is shown.