What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Social science
- World Wide Web
His main research concerns Data science, Information visualization, Visualization, Information retrieval and Scientometrics.
His studies in Data science integrate themes in fields like Context, Knowledge management, Intellectual structure, Data visualization and Project management.
His work in Information visualization addresses issues such as Empirical research, which are connected to fields such as Selection.
His Visualization study combines topics from a wide range of disciplines, such as Domain and Usability, Human–computer interaction.
His Information retrieval research integrates issues from Hypertext, World Wide Web, Citation, Field and Pathfinder network.
His studies examine the connections between Scientometrics and genetics, as well as such issues in Citation analysis, with regards to Adaptation, Bibliometrics and Science policy.
His most cited work include:
- CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature (1218 citations)
- Visualizing knowledge domains (838 citations)
- Searching for intellectual turning points: Progressive knowledge domain visualization (604 citations)
What are the main themes of his work throughout his whole career to date?
Chaomei Chen focuses on Data science, Visualization, Information visualization, Information retrieval and Citation.
His Data science research includes elements of Visual analytics, Structure, Variety and Sociology of scientific knowledge.
His Visualization research is multidisciplinary, incorporating perspectives in Domain, World Wide Web and Human–computer interaction.
Chaomei Chen has researched Information visualization in several fields, including Graph drawing and Information space.
His work in the fields of Citation, such as Citation analysis, intersects with other areas such as Systematic review.
His Citation analysis research incorporates elements of Information science, Bibliometrics and Scientometrics.
He most often published in these fields:
- Data science (36.63%)
- Visualization (26.74%)
- Information visualization (21.25%)
What were the highlights of his more recent work (between 2015-2021)?
- Data science (36.63%)
- Citation (16.48%)
- Scientometrics (9.52%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Data science, Citation, Scientometrics, Sociology of scientific knowledge and Citation analysis.
His work deals with themes such as Information science, Data collection, Structure, Range and Variety, which intersect with Data science.
His Citation research incorporates themes from Search engine indexing and Pace.
His research integrates issues of Visual analytics and Visualization in his study of Scientometrics.
Context and Information retrieval is closely connected to Bibliometrics in his research, which is encompassed under the umbrella topic of Citation analysis.
The concepts of his Information retrieval study are interwoven with issues in Information visualization, Geovisualization and Data visualization.
Between 2015 and 2021, his most popular works were:
- Science Mapping: A Systematic Review of the Literature (210 citations)
- Visualizing a field of research: A methodology of systematic scientometric reviews. (76 citations)
- Visualizing a field of research: A methodology of systematic scientometric reviews. (76 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Social science
- World Wide Web
Data science, Scientometrics, Sociology of scientific knowledge, Data visualization and Information retrieval are his primary areas of study.
His work carried out in the field of Data science brings together such families of science as Computational linguistics, Scalability and Subject-matter expert.
His Scientometrics study combines topics in areas such as Nanoparticle and Drug delivery.
The Sociology of scientific knowledge study combines topics in areas such as Resource, Variety, Deep learning, Artificial intelligence and Semantic equivalence.
His biological study deals with issues like Review article, which deal with fields such as Bibliometrics, Citation analysis and Citation.
His Information retrieval research is multidisciplinary, relying on both Biological data visualization, Interactive visual analysis, Visualization, Information visualization and Geovisualization.
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