Identifying Anomalous Citations for Objective Evaluation of Scholarly Article Impact.
Evaluating the impact of a scholarly article is of great significance and has attracted great attentions. Although citation-based evaluation approaches have been widely used, these approaches face limitations e.g. in identifying anomalous citations patterns. This negligence would inevitably cause un...
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doaj-c7e1afff9ee040788335ffa79b76287b2020-11-24T22:20:04ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01119e016236410.1371/journal.pone.0162364Identifying Anomalous Citations for Objective Evaluation of Scholarly Article Impact.Xiaomei BaiFeng XiaIvan LeeJun ZhangZhaolong NingEvaluating the impact of a scholarly article is of great significance and has attracted great attentions. Although citation-based evaluation approaches have been widely used, these approaches face limitations e.g. in identifying anomalous citations patterns. This negligence would inevitably cause unfairness and inaccuracy to the article impact evaluation. In this study, in order to discover the anomalous citations and ensure the fairness and accuracy of research outcome evaluation, we investigate the citation relationships between articles using the following factors: collaboration times, the time span of collaboration, citing times and the time span of citing to weaken the relationship of Conflict of Interest (COI) in the citation network. Meanwhile, we study a special kind of COI, namely suspected COI relationship. Based on the COI relationship, we further bring forward the COIRank algorithm, an innovative scheme for accurately assessing the impact of an article. Our method distinguishes the citation strength, and utilizes PageRank and HITS algorithms to rank scholarly articles comprehensively. The experiments are conducted on the American Physical Society (APS) dataset. We find that about 80.88% articles contain contributed citations by co-authors in 26,366 articles and 75.55% articles among these articles are cited by the authors belonging to the same affiliation, indicating COI and suspected COI should not be ignored for evaluating impact of scientific papers objectively. Moreover, our experimental results demonstrate COIRank algorithm significantly outperforms the state-of-art solutions. The validity of our approach is verified by using the probability of Recommendation Intensity.http://europepmc.org/articles/PMC5015995?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiaomei Bai Feng Xia Ivan Lee Jun Zhang Zhaolong Ning |
spellingShingle |
Xiaomei Bai Feng Xia Ivan Lee Jun Zhang Zhaolong Ning Identifying Anomalous Citations for Objective Evaluation of Scholarly Article Impact. PLoS ONE |
author_facet |
Xiaomei Bai Feng Xia Ivan Lee Jun Zhang Zhaolong Ning |
author_sort |
Xiaomei Bai |
title |
Identifying Anomalous Citations for Objective Evaluation of Scholarly Article Impact. |
title_short |
Identifying Anomalous Citations for Objective Evaluation of Scholarly Article Impact. |
title_full |
Identifying Anomalous Citations for Objective Evaluation of Scholarly Article Impact. |
title_fullStr |
Identifying Anomalous Citations for Objective Evaluation of Scholarly Article Impact. |
title_full_unstemmed |
Identifying Anomalous Citations for Objective Evaluation of Scholarly Article Impact. |
title_sort |
identifying anomalous citations for objective evaluation of scholarly article impact. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2016-01-01 |
description |
Evaluating the impact of a scholarly article is of great significance and has attracted great attentions. Although citation-based evaluation approaches have been widely used, these approaches face limitations e.g. in identifying anomalous citations patterns. This negligence would inevitably cause unfairness and inaccuracy to the article impact evaluation. In this study, in order to discover the anomalous citations and ensure the fairness and accuracy of research outcome evaluation, we investigate the citation relationships between articles using the following factors: collaboration times, the time span of collaboration, citing times and the time span of citing to weaken the relationship of Conflict of Interest (COI) in the citation network. Meanwhile, we study a special kind of COI, namely suspected COI relationship. Based on the COI relationship, we further bring forward the COIRank algorithm, an innovative scheme for accurately assessing the impact of an article. Our method distinguishes the citation strength, and utilizes PageRank and HITS algorithms to rank scholarly articles comprehensively. The experiments are conducted on the American Physical Society (APS) dataset. We find that about 80.88% articles contain contributed citations by co-authors in 26,366 articles and 75.55% articles among these articles are cited by the authors belonging to the same affiliation, indicating COI and suspected COI should not be ignored for evaluating impact of scientific papers objectively. Moreover, our experimental results demonstrate COIRank algorithm significantly outperforms the state-of-art solutions. The validity of our approach is verified by using the probability of Recommendation Intensity. |
url |
http://europepmc.org/articles/PMC5015995?pdf=render |
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