Authorship Patterns and Citation Dynamics in Quantum Physics:A Bibliometric and Machine Learning Analysis

Huijing Huang

doi:10.47297/taposatWSP2633-456915.20260705

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Authorship Patterns and Citation Dynamics in Quantum Physics:A Bibliometric and Machine Learning Analysis

Volume 7, Issue 5

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Authorship Patterns and Citation Dynamics in Quantum Physics:A Bibliometric and Machine Learning Analysis
Authorship Patterns and Citation Dynamics in Quantum Physics:A Bibliometric and Machine Learning Analysis
The Experimental High School Attached to Beijing Normal University, Beijing, 100000, China
Vol. 7, Issue 5, Pages: 77-80(2026)
Online First：15 July 2026，

Published：30 May 2026
DOI：10.47297/taposatWSP2633-456915.20260705
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Huang Huijing.Authorship Patterns and Citation Dynamics in Quantum Physics:A Bibliometric and Machine Learning Analysis[J].Theory and Practice of Science and Technology,2026,07(05):77-80.
DOI：

Huang Huijing.Authorship Patterns and Citation Dynamics in Quantum Physics:A Bibliometric and Machine Learning Analysis[J].Theory and Practice of Science and Technology,2026,07(05):77-80. DOI： 10.47297/taposatWSP2633-456915.20260705.

摘要

Abstract

This study presents a bibliometric analysis of authorship and citation patterns in quantum physics research published between 1995 and 2015. Using a gender inference model achieving 92.7% accuracy

we analyze first authorship rates

citation frequency

Time to First Citation (TTFC)

temporal PageRank centrality

and self-citation behavior across demographic dimensions including gender

academic age

and geographic origin. Machine learning and network analysis methods are employed to identify systematic patterns in publication and citation dynamics. Results reveal notable variations in citation metrics across demographic groups

with intersecting factors such as age and nationality showing compound effects. Policy interventions are briefly reviewed. These findings contribute to a data-driven understanding of authorship dynamics in quantum physics.

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references

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