Research Article: Quantifying the impact of scholarly papers based on higher-order weighted citations

Date Published: March 29, 2018

Publisher: Public Library of Science

Author(s): Xiaomei Bai, Fuli Zhang, Jie Hou, Ivan Lee, Xiangjie Kong, Amr Tolba, Feng Xia, Wolfgang Glanzel.

http://doi.org/10.1371/journal.pone.0193192

Abstract

Quantifying the impact of a scholarly paper is of great significance, yet the effect of geographical distance of cited papers has not been explored. In this paper, we examine 30,596 papers published in Physical Review C, and identify the relationship between citations and geographical distances between author affiliations. Subsequently, a relative citation weight is applied to assess the impact of a scholarly paper. A higher-order weighted quantum PageRank algorithm is also developed to address the behavior of multiple step citation flow. Capturing the citation dynamics with higher-order dependencies reveals the actual impact of papers, including necessary self-citations that are sometimes excluded in prior studies. Quantum PageRank is utilized in this paper to help differentiating nodes whose PageRank values are identical.

Partial Text

With the rapidly growth of scholarly big data [1], there’s a crucial need to quantify the impact of scholarly papers, to assess the performance of individual scholars, institutions, even for countries [2]. Currently, the impact of scholarly paper is mainly divided into two categories: unstructured metrics and structured metrics [3]. Unstructured metrics evaluate the impact of scholarly paper from a statistical point of view. Citations [4] [5] are the most representative unstructured metrics, with examples such as the H-index [6], the g-index [7], and the impact factor (IF) [8]. As an alternative measure of scientific impact, Xia et al. [9] have investigated scholarly impact reflected on social media, and explore the correlation between citations and messages/tweets on Facebook and Tweeter. The structured metrics mainly consider the importance of scholarly entities in scholarly network, such as citation network, co-authors network, author-paper network, etc. PageRank [10], a seminal example of structured metrics, has attracted growing attentions in scholarly impact evaluation. Sayyadi et al. [11] have estimated future prestige scores of scholarly papers via the following three features: citations, publication date, and authorship. Wang et al. [12] have quantified the impact of scholarly papers by applying PageRank and HITS [13] on citation network, author-paper network, and journal-paper network. In the unweighted structured metrics, all citations are treated with equal importance. An alternative approach is to evaluate the impact of scholarly papers by time-aware weighted citation network [14]. In another study, Shah et al. [15] has proposed the S-index metric to model the influence prorogation by a weighted paper-paper citation networks. This paper applies a hierarchical model between the citing paper and the cited paper, thus the impact of a scholarly paper decayed rapidly over different hierarchical levels.

 

Source:

http://doi.org/10.1371/journal.pone.0193192

 

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