C
Chao Lu
Researcher at Hohai University
Publications - 15
Citations - 155
Chao Lu is an academic researcher from Hohai University. The author has contributed to research in topics: Linguistic sequence complexity & Citation. The author has an hindex of 5, co-authored 14 publications receiving 81 citations. Previous affiliations of Chao Lu include Nanjing University of Science and Technology & Indiana University.
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Analyzing linguistic complexity and scientific impact
Chao Lu,Yi Bu,Xianlei Dong,Jie Wang,Ying Ding,Vincent Larivière,Cassidy R. Sugimoto,Logan Paul,Chengzhi Zhang +8 more
TL;DR: 12 variables of linguistic complexity were selected as a proxy for depicting scientific writing and compared to the scientific impact of articles, suggesting that textual complexity plays little role in scientific impact in data sets.
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Understanding the impact change of a highly cited article: a content-based citation analysis
TL;DR: Investigation of how one highly cited essay, Hirsch’s “h-index” article (H-article) published in 2005, has been cited by other articles confirms that citation context captures the changing impact of the H-article over time in several ways.
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Examining scientific writing styles from the perspective of linguistic complexity
Chao Lu,Chao Lu,Yi Bu,Jie Wang,Ying Ding,Ying Ding,Vetle I. Torvik,Matthew Schnaars,Chengzhi Zhang +8 more
TL;DR: This paper examined the scientific writing styles in English from a two-fold perspective of linguistic complexity: syntactic complexity, including measurements of sentence length and sentence complexity; and lexical complexity, measuring lexical diversity, lexical density, and Lexical sophistication.
Posted Content
Analyzing Linguistic Complexity and Scientific Impact
Chao Lu,Yi Bu,Xianlei Dong,Jie Wang,Ying Ding,Vincent Larivière,Cassidy R. Sugimoto,Logan Paul,Chengzhi Zhang +8 more
TL;DR: This article analyzed the relationship between scientific writing and scientific impact and found no practical significant relationship between linguistic complexity and citation strata in either discipline, which suggests that textual complexity plays little role in scientific impact in their data sets.
Journal ArticleDOI
Analyzing knowledge entities about COVID-19 using entitymetrics.
Qi Yu,Qi Wang,Yafei Zhang,Chongyan Chen,Hyeyoung Ryu,Namu Park,Jae Eun Baek,Keyuan Li,Yifei Wu,Daifeng Li,Jian Xu,Meijun Liu,Jeremy J. Yang,Chenwei Zhang,Chao Lu,Peng Zhang,Xin Li,Baitong Chen,Islam Akef Ebeid,Julia Fensel,Chao Min,Yujia Zhai,Yujia Zhai,Min Song,Ying Ding,Yi Bu +25 more
TL;DR: In this paper, an entity-entity co-occurrence network was constructed and network indicators were employed to analyze the extracted entities. But none of the analyses have focused on domain entities occurring in scientific publications.