Citation Structural Diversity: A Novel and Concise Metric Combining Structure and Semantics for Literature Evaluation

TL;DR

This paper proposes a new metric called citation structural diversity that combines network structure and semantic information to improve literature evaluation by capturing interdisciplinarity and long-term impact.

Contribution

It introduces a novel citation evaluation model that integrates structural and semantic features, enhancing assessment of academic influence and interdisciplinarity.

Findings

Higher citation structural diversity correlates with increased citation frequency.

Literature with greater structural diversity shows more sustained academic impact.

The model effectively captures interdisciplinarity in citation networks.

Abstract

As academic research becomes increasingly diverse, traditional literature evaluation methods face significant limitations,particularly in capturing the complexity of academic dissemination and the multidimensional impacts of literature. To address these challenges, this paper introduces a novel literature evaluation model of citation structural diversity, with a focus on assessing its feasibility as an evaluation metric. By refining citation network and incorporating both ciation structural features and semantic information, the study examines the influence of the proposed model of citation structural diversity on citation volume and long-term academic impact. The findings reveal that literature with higher citation structural diversity demonstrates notable advantages in both citation frequency and sustained academic influence. Through data grouping and a decade-long citation trend analysis, the potential application of this model in literature evaluation is further validated. This research offers a fresh perspective on optimizing literature evaluation methods and emphasizes the distinct advantages of citation structural diversity in measuring interdisciplinarity.