The paper by S. Redner examines the distribution of citations for scientific papers, focusing on two large datasets: (i) 783,339 papers published in 1981 by the Institute for Scientific Information (ISI), and (ii) 24,296 papers in Physical Review D from 1975 to 1994. The author investigates the citation distribution, particularly the number of papers cited \( x \) times, denoted as \( N(x) \). Using Zipf plots and moment comparisons, Redner finds that the citation distribution has a power-law tail, \( N(x) \sim x^{-\alpha} \), with \( \alpha \approx 3 \). This suggests that the distribution is not described by a single function over the entire range of citation counts. The study also highlights the temporal evolution of citation statistics, noting that the average number of citations per paper decreases over time, while the total number of citations increases. The findings provide insights into the popularity and recognition of scientific publications and suggest the need for further research on older citation data and theoretical models to better understand the distribution of citations.The paper by S. Redner examines the distribution of citations for scientific papers, focusing on two large datasets: (i) 783,339 papers published in 1981 by the Institute for Scientific Information (ISI), and (ii) 24,296 papers in Physical Review D from 1975 to 1994. The author investigates the citation distribution, particularly the number of papers cited \( x \) times, denoted as \( N(x) \). Using Zipf plots and moment comparisons, Redner finds that the citation distribution has a power-law tail, \( N(x) \sim x^{-\alpha} \), with \( \alpha \approx 3 \). This suggests that the distribution is not described by a single function over the entire range of citation counts. The study also highlights the temporal evolution of citation statistics, noting that the average number of citations per paper decreases over time, while the total number of citations increases. The findings provide insights into the popularity and recognition of scientific publications and suggest the need for further research on older citation data and theoretical models to better understand the distribution of citations.