Citation networks in high energy physics.

Area of Science:

• Bibliometrics
• Physics
• Information Science

Background:

• Citation networks are crucial for understanding scientific impact.
• Empirical analysis of citation data reveals underlying network structures.

Purpose of the Study:

• To empirically investigate the citation network within the SPIRES database.
• To model citation probability distributions using power laws.
• To analyze the homogeneity of citation patterns in high energy physics.

Main Methods:

• Empirical analysis of the SPIRES database citation network.
• Statistical modeling using power laws to describe citation distributions.
• Subfield analysis focusing on high energy physics.

Main Results:

• Citation probability follows power laws: P(k) ~ k^-1.2 for k<50 and P(k) ~ k^-2.3 for k>=50.
• High energy physics exhibits a remarkably homogeneous citation network.
• Citation records of individuals/institutions are highly unlikely to be random draws.

Conclusions:

• Citation distributions in physics databases are non-random and follow predictable power-law patterns.
• The homogeneity in high energy physics suggests strong community ties.
• This analysis provides a framework for evaluating the statistical significance of citation metrics.