Document Type : Original Article

Authors

• saeedeh mirhaghjoo ¹
• farshid danesh ²
• fatemeh Alinezhad chamazcoti ²

¹ Department of Information Management, Islamic World Science and Technology Monitoring and Citation Institute (ISC), Shiraz, Iran

² , Department of Information Management, Islamic World Science and Technology Monitoring and Citation Institute (ISC), Shiraz, Iran

Abstract

Abstract
Objective: This study examined the relationship between conventional research evaluation indicators measured at the researcher and article levels and the structural dimensions of ego-centered citation networks for highly cited papers authored by Iranian computer scientists.
Methods: An applied analytical scientometric design was used. Lists of Iranian researchers ranked among the top one and two percent in computer science were merged and duplicates removed. The analysis covered 219 highly cited papers associated with 44 researchers during 2013–2024. For each focal paper, an ego-centered citation network was constructed. Absolute and relative measures of depth, breadth, dependence, and independence were calculated. Spearman rank correlations were used to evaluate associations.
Findings: Academic rank and publication count were not significantly associated with any structural indicators. The h-index was significantly and positively associated with relative depth. Article citation counts had significant positive correlations with absolute depth, relative depth, and absolute dependence, with coefficients of 0.329, 0.408, and 0.430, respectively.
Conclusion: Conventional indicators and structural dimensions do not describe identical aspects of citation impact. A larger citation count does not necessarily imply corresponding changes in every characteristic of a citation network. Structural analysis can complement traditional indicators by clarifying how citation relationships are organized. As the study is correlational, the findings do not establish causal relationships.
Keywords: Research Evaluation; Bibliometric Indicators; Spearman's Rank Correlation; Scientific Impact; Network Analysis.

Keywords

• Research Evaluation
• Bibliometric Indicators
• Spearman's Rank Correlation
• Scientific Impact
• Network Analysis

Main Subjects

• Sociological and Anthropological Dimensions of Data, Information and Knowledge Studies