Journal article
Detecting evolution of bioinformatics with a content and co-authorship analysis
SpringerPlus, v 2(1), pp 1-11
Dec 2013
PMID: 23710427
Abstract
Bioinformatics is an interdisciplinary research field that applies advanced computational techniques to biological data. Bibliometrics analysis has recently been adopted to understand the knowledge structure of a research field by citation pattern. In this paper, we explore the knowledge structure of Bioinformatics from the perspective of a core open access Bioinformatics journal, BMC Bioinformatics with trend analysis, the content and co-authorship network similarity, and principal component analysis. Publications in four core journals including Bioinformatics – Oxford Journal and four conferences in Bioinformatics were harvested from DBLP. After converting publications into TF-IDF term vectors, we calculate the content similarity, and we also calculate the social network similarity based on the co-authorship network by utilizing the overlap measure between two co-authorship networks. Key terms is extracted and analyzed with PCA, visualization of the co-authorship network is conducted. The experimental results show that Bioinformatics is fast-growing, dynamic and diversified. The content analysis shows that there is an increasing overlap among Bioinformatics journals in terms of topics and more research groups participate in researching Bioinformatics according to the co-authorship network similarity.
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Details
- Title
- Detecting evolution of bioinformatics with a content and co-authorship analysis
- Creators
- Min Song - Department of Library and Information Science, Yonsei University, Seoul, South KoreaChristopher C Yang - College of Information Science and Technology Drexel University Philadelphia, Philadelphia, PA 19104 USAXuning Tang - College of Information Science and Technology Drexel University Philadelphia, Philadelphia, PA 19104 USA
- Publication Details
- SpringerPlus, v 2(1), pp 1-11
- Publisher
- Springer International Publishing; Cham
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000209461900186
- Scopus ID
- 2-s2.0-84878773190
- Other Identifier
- 991014877838104721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Information Science & Library Science