Advances and Applications in Discrete Mathematics

The Advances and Applications in Discrete Mathematics is a prestigious peer-reviewed journal indexed in the Emerging Sources Citation Index (ESCI). It is dedicated to publishing original research articles in the field of discrete mathematics and combinatorics, including topics such as graphs, coding theory, and block design. The journal emphasizes efficient and powerful tools for real-world applications and welcomes expository articles that highlight current developments in the field.

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PAPER CITATION NETWORK ANALYSIS ON THEORETICAL HIGH ENERGY PHYSICS

Authors

  • Jonecis Dayap
  • Victor Barraza
  • Jeanilyn Dionsay
  • Richard Alcantara
  • Temidayo Joseph Oluwafemi

Keywords:

citation network, theoretical high energy, network metrics.

DOI:

https://doi.org/10.17654/0974165822020%20

Abstract

The current research examines the theoretical high energy physics (THEP) citation network. It shows that the THEP can be divided into five major subfields. The in-degree distribution of THEP exhibits a power-law distribution, indicating the presence of a hub. The results of the calculated metrics suggest that the network is efficient, and information can easily flow across the network. However, there is a slight connection between papers having similar reference lists. Finally, there is a weak association between in-degree and out-degree metrics, showing that increasing the number of papers cited in the reference list does not result in more paper citations.

Received: February 2, 2022
Accepted: March 3, 2022

References

References

S. Dawson, D. Gasevic, G. Siemens and S. Joksimovic, Current state and future trends: A citation network analysis of the learning analytics field, Proceedings of the fourth International Conference on Learning Analytics and Knowledge, 2014, pp. 231-240.

Y. Kajikawa and Y. Takeda, Citation network analysis of organic LEDs, Technological Forecasting and Social Change 76(8) (2009), 1115-1123.

S. Lehmann, B. Lautrup and A. D. Jackson, Citation networks in high energy physics, Physical Review E 68(2) (2003), 026113.

J. Leskovec and A. Krevl, SNAP Datasets: Stanford Large Network Dataset Collection, 2014. http://snap.stanford.edu/data

D. H. Perkins and D. H. Perkins, Introduction to High Energy Physics, Cambridge University Press, 2000.

K. Y. Tang, C. Y. Chang and G. J. Hwang, Trends in artificial intelligence- supported e-learning: A systematic review and co-citation network analysis (1998-2019), Interactive Learning Environments (2021), 1-19.

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Published

2022-03-03

Issue

Vol. 30 (2022)

Section

Articles

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Copyright (c) 2022 PUSHPA PUBLISHING HOUSE, PRAYAGRAJ, INDIA

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How to Cite

PAPER CITATION NETWORK ANALYSIS ON THEORETICAL HIGH ENERGY PHYSICS. (2022). Advances and Applications in Discrete Mathematics, 30, 81-86. https://doi.org/10.17654/0974165822020

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