Best Scholar Award
Dan Chen, Wuhan Textile University, China
The Best Scholar Award recognizes scholarly work demonstrating sustained research activity, academic contribution, and measurable research influence. Dan Chen is presented in this academic recognition profile in connection with Wuhan Textile University and the field of Information Science. [1]
Abstract
Dan Chen is identified with Wuhan Textile University and Information Science, with 15 indexed documents, 196 citations, and an h-index of 8 in the supplied Scopus record. These indicators provide a concise quantitative description of scholarly visibility and citation performance within the indexed research literature.[1]
Keywords
Dan Chen; Best Scholar Award; Information Science; scholarly communication; research impact; bibliometrics; academic publications; citation analysis; Wuhan Textile University; Cryogenicist Global Awards.
Introduction
Bibliometric databases are widely used to organize scholarly records and evaluate publication and citation patterns. Scopus provides author-level information that can assist researchers and institutions in examining publication output, citations, and related indicators.[2]
Research Profile
The supplied profile associates Dan Chen with Information Science at Wuhan Textile University. The reported Scopus identifier provides a persistent route for distinguishing the researcher’s indexed record, while the ORCID identifier provides an additional persistent digital identifier intended to support accurate attribution across scholarly activities.[3]
Research Contributions
A researcher’s contribution is best understood through the combined examination of scholarly outputs, research themes, collaboration, methodological development, and influence within the relevant literature. The available profile data establish a measurable publication and citation record, while detailed contribution assessment requires examination of individual publications.[4]
Publications
The supplied Scopus record reports 15 documents associated with the researcher identifier. Individual publication titles, journals, publication dates, co-authorship networks, and subject-specific citation patterns should be verified directly through the indexed author profile and corresponding publisher records before being used for formal bibliographic evaluation.[1]
Research Impact
The reported 196 citations and h-index of 8 indicate that the indexed publication set has received measurable scholarly attention. Citation indicators are informative but do not independently establish research quality, originality, or societal significance; responsible assessment therefore benefits from complementary qualitative evidence and disciplinary benchmarks.[5]
Award Suitability
For the Best Scholar Award, the supplied record offers objective indicators that may support consideration of scholarly productivity and research visibility. Final award suitability should also incorporate verified publication quality, originality, contribution to the field, peer recognition, and the award’s formal evaluation criteria.[4]
Conclusion
Dan Chen’s supplied academic profile records 15 documents, 196 citations, and an h-index of 8 in Information Science, alongside persistent Scopus and ORCID identifiers. These data provide a concise basis for an academic recognition profile, while comprehensive evaluation should consider both quantitative indicators and substantive scholarly evidence.[2]
External Links
References
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- Elsevier. (n.d.). Scopus author details: Dan Chen, Author ID 57206581510. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=57206581510
- ORCID. (n.d.). ORCID record for Dan Chen. ORCID.
https://orcid.org/0000-0001-5611-1541
- Elsevier. (n.d.). Information Sciences: Framework based on communicability to measure the similarity of nodes in complex networks. ScienceDirect.
https://doi.org/10.1016/j.ins.2020.03.046
- IEEE. (2023). Scaling properties of scale-free networks in degree-thresholding renormalization flows. IEEE Transactions on Network Science and Engineering.
https://doi.org/10.1109/TNSE.2023.3266381
- American Physical Society. (2021). Finite-size scaling of geometric renormalization flows in complex networks. Physical Review E.https://doi.org/10.1103/PhysRevE.104.034304