Kevin Boyack - Academia.edu (original) (raw)

Papers by Kevin Boyack

PLOS One, 2017

We aimed to assess which factors correlate with collaborative behavior and whether such behavior... more We aimed to assess which factors correlate with collaborative behavior and whether such behavior associates with scientific impact (citations and becoming a principal investigator). We used the R index which is defined for each author as log(Np)/log(I1), where I1 is the number of co-authors who appear in at least I1 papers written by that author and Np are his/her total papers. Higher R means lower collaborative behavior, i.e. not working much with others, or not collaborating repeatedly with the same co-authors. Across 249,054 researchers who had published ≥30 papers in 2000-2015 but had not published anything before 2000, R varied across scientific fields. Lower values of R (more collaboration) were seen in physics, medicine, infectious disease and brain sciences and higher values of R were seen for social science, computer science and engineering. Among the 9,314 most productive researchers already reaching Np ≥ 30 and I1 ≥ 4 by the end of 2006, R mostly remained stable for most fields from 2006 to 2015 with small increases seen in physics, chemistry, and medicine. Both US-based authorship and male gender were associated with higher values of R (lower collaboration), although the effect was small. Lower values of R (more collaboration) were associated with higher citation impact (h-index), and the effect was stronger in certain fields (physics, medicine, engineering, health sciences) than in others (brain sciences, computer science, infectious disease, chemistry). Finally, for a subset of 400 U.S. researchers in medicine, infectious disease and brain sciences, higher R (lower collaboration) was associated with a higher chance of being a principal investigator by 2016. Our analysis maps the patterns and evolution of collaborative behavior across scientific disciplines.

We introduce a framework for understanding knowledge production in which: knowledge is produced i... more We introduce a framework for understanding knowledge production in which: knowledge is produced in stages (along a research to development continuum) and in three discrete categories (science and understanding, tools and technology, and societal use and behavior); and knowledge in the various stages and categories is produced both non-interactively and interactively. The framework attempts to balance: our experiences as working scientists and technologists, our best current understanding of the social processes of knowledge production, and the possibility of mathematical analyses. It offers a potential approach both to improving our basic understanding, and to developing tools for enterprise management, of the knowledge-production process. Published by Elsevier B.V.

Bulletin of the American Society for Information Science and Technology, 2015

ABSTRACT EDITOR'S SUMMARYThe science mapping community offers insights and points to tren... more ABSTRACT EDITOR'S SUMMARYThe science mapping community offers insights and points to trends in scientific inquiry by revealing connections among publications, authors, terminology and citation patterns. The authors applied the process of creating science maps to topics compiled by GuideStar to reveal altruistic motives driving nonprofit organizations (NPOs). From data mined from nearly four million web pages from 125,000 NPO websites, they created a map of the altruistic motive space. Topic modeling from words on the web pages generated 1,000 topics that were manually screened to yield 357 topics related to altruistic motives and their interrelationships. Nearly 100,000 NPOs were positioned by topic on an overlay map, and map labels capturing altruistic motives were created by human analysis. The product was compared with a map of science based on Elsevier's Scopus database. The maps of altruism and science show the strongest link between the altruistic trait of caring and scientific research in medicine, health and neuroscience. Links are also demonstrated between other scientific areas and altruistic beliefs underlying environment, innovation and policy.

Bulletin of the American Society for Information Science and Technology, 2015

ABSTRACT EDITOR'S SUMMARYFrom early cartography to modern science maps, visual presentati... more ABSTRACT EDITOR'S SUMMARYFrom early cartography to modern science maps, visual presentations facilitate understanding of large amounts of data. A traveling exhibit entitled Places and Spaces: Mapping Science has presented outstanding maps illustrating different designs and applications since 2005. The 10th year of the exhibit focuses on the future of science mapping and features five maps described in this special section of the Bulletin. Topics include the history of physics and key contributors, the development of the Internet and the structure of fields and topics in science and technology. Each emerged from latent relationships among elements in large volumes of data, made clear through visualization in an easily understandable format. Given high quality data, processing tools, design and analysis expertise and research funding, science mapping can be expected to expand in application and usefulness. Key challenges include insufficient numbers of experts, lack of sophisticated tools, low literacy in data visualization and absence of design standards.

Journal of the Association for Information Science and Technology, 2013

PLOS One, 2017

We aimed to assess which factors correlate with collaborative behavior and whether such behavior... more We aimed to assess which factors correlate with collaborative behavior and whether such behavior associates with scientific impact (citations and becoming a principal investigator). We used the R index which is defined for each author as log(Np)/log(I1), where I1 is the number of co-authors who appear in at least I1 papers written by that author and Np are his/her total papers. Higher R means lower collaborative behavior, i.e. not working much with others, or not collaborating repeatedly with the same co-authors. Across 249,054 researchers who had published ≥30 papers in 2000-2015 but had not published anything before 2000, R varied across scientific fields. Lower values of R (more collaboration) were seen in physics, medicine, infectious disease and brain sciences and higher values of R were seen for social science, computer science and engineering. Among the 9,314 most productive researchers already reaching Np ≥ 30 and I1 ≥ 4 by the end of 2006, R mostly remained stable for most fields from 2006 to 2015 with small increases seen in physics, chemistry, and medicine. Both US-based authorship and male gender were associated with higher values of R (lower collaboration), although the effect was small. Lower values of R (more collaboration) were associated with higher citation impact (h-index), and the effect was stronger in certain fields (physics, medicine, engineering, health sciences) than in others (brain sciences, computer science, infectious disease, chemistry). Finally, for a subset of 400 U.S. researchers in medicine, infectious disease and brain sciences, higher R (lower collaboration) was associated with a higher chance of being a principal investigator by 2016. Our analysis maps the patterns and evolution of collaborative behavior across scientific disciplines.

We introduce a framework for understanding knowledge production in which: knowledge is produced i... more We introduce a framework for understanding knowledge production in which: knowledge is produced in stages (along a research to development continuum) and in three discrete categories (science and understanding, tools and technology, and societal use and behavior); and knowledge in the various stages and categories is produced both non-interactively and interactively. The framework attempts to balance: our experiences as working scientists and technologists, our best current understanding of the social processes of knowledge production, and the possibility of mathematical analyses. It offers a potential approach both to improving our basic understanding, and to developing tools for enterprise management, of the knowledge-production process. Published by Elsevier B.V.

Bulletin of the American Society for Information Science and Technology, 2015

ABSTRACT EDITOR'S SUMMARYThe science mapping community offers insights and points to tren... more ABSTRACT EDITOR'S SUMMARYThe science mapping community offers insights and points to trends in scientific inquiry by revealing connections among publications, authors, terminology and citation patterns. The authors applied the process of creating science maps to topics compiled by GuideStar to reveal altruistic motives driving nonprofit organizations (NPOs). From data mined from nearly four million web pages from 125,000 NPO websites, they created a map of the altruistic motive space. Topic modeling from words on the web pages generated 1,000 topics that were manually screened to yield 357 topics related to altruistic motives and their interrelationships. Nearly 100,000 NPOs were positioned by topic on an overlay map, and map labels capturing altruistic motives were created by human analysis. The product was compared with a map of science based on Elsevier's Scopus database. The maps of altruism and science show the strongest link between the altruistic trait of caring and scientific research in medicine, health and neuroscience. Links are also demonstrated between other scientific areas and altruistic beliefs underlying environment, innovation and policy.

Bulletin of the American Society for Information Science and Technology, 2015

ABSTRACT EDITOR'S SUMMARYFrom early cartography to modern science maps, visual presentati... more ABSTRACT EDITOR'S SUMMARYFrom early cartography to modern science maps, visual presentations facilitate understanding of large amounts of data. A traveling exhibit entitled Places and Spaces: Mapping Science has presented outstanding maps illustrating different designs and applications since 2005. The 10th year of the exhibit focuses on the future of science mapping and features five maps described in this special section of the Bulletin. Topics include the history of physics and key contributors, the development of the Internet and the structure of fields and topics in science and technology. Each emerged from latent relationships among elements in large volumes of data, made clear through visualization in an easily understandable format. Given high quality data, processing tools, design and analysis expertise and research funding, science mapping can be expected to expand in application and usefulness. Key challenges include insufficient numbers of experts, lack of sophisticated tools, low literacy in data visualization and absence of design standards.

Journal of the Association for Information Science and Technology, 2013