What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Social science
Kevin W. Boyack mainly focuses on Citation, Information retrieval, Data science, Citation analysis and Visualization.
His Citation study frequently draws connections between adjacent fields such as Scientometrics.
His research integrates issues of Bibliographic coupling and VxInsight, Bioinformatics in his study of Information retrieval.
Kevin W. Boyack focuses mostly in the field of Bibliographic coupling, narrowing it down to topics relating to Co-citation and, in certain cases, Data mining.
Kevin W. Boyack studied Bioinformatics and Similarity matrix that intersect with Graph.
His research investigates the link between Data science and topics such as Social science that cross with problems in Similarity.
His most cited work include:
- Visualizing knowledge domains (838 citations)
- Mapping the backbone of science (611 citations)
- Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature (425 citations)
What are the main themes of his work throughout his whole career to date?
Kevin W. Boyack mainly investigates Citation, Information retrieval, Data science, Citation analysis and Cluster analysis.
His Citation study introduces a deeper knowledge of Library science.
His Information retrieval research includes themes of Bibliographic coupling, Similarity, VxInsight and Data mining.
His Data science research incorporates themes from Field and Social science, Scientometrics.
The Citation analysis study combines topics in areas such as Quality and Bibliometrics.
His Cluster analysis research is multidisciplinary, incorporating perspectives in Similarity, Graph Layout and Graph.
He most often published in these fields:
- Citation (29.73%)
- Information retrieval (28.83%)
- Data science (24.32%)
What were the highlights of his more recent work (between 2017-2021)?
- Citation (29.73%)
- Information retrieval (28.83%)
- Data science (24.32%)
In recent papers he was focusing on the following fields of study:
His main research concerns Citation, Information retrieval, Data science, Citation analysis and Library science.
Kevin W. Boyack has included themes like Rhetorical question and Interpretation in his Citation study.
His studies in Information retrieval integrate themes in fields like Bibliographic coupling, Similarity and Cluster analysis.
His Cluster analysis research integrates issues from Consistency and Similarity.
His studies deal with areas such as Field and Futures studies as well as Data science.
His research investigates the connection between Citation analysis and topics such as Bibliometrics that intersect with problems in Sentence.
Between 2017 and 2021, his most popular works were:
- Reproducible research practices, transparency, and open access data in the biomedical literature, 2015-2017. (90 citations)
- A standardized citation metrics author database annotated for scientific field (72 citations)
- Thousands of scientists publish a paper every five days (70 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Social science
His primary scientific interests are in Bibliometrics, Information retrieval, Citation, Citation analysis and Scientific field.
His Bibliometrics study integrates concerns from other disciplines, such as Sentence, Social science, Similarity and Co-citation.
His study connects Paragraph and Information retrieval.
Citation and Composite indicator are two areas of study in which Kevin W. Boyack engages in interdisciplinary research.
His Scientific field study spans across into subjects like Scale analysis, Interval, Research questions, Scientific publishing and Field.
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