Laying the Foundations for Scientometric Research: A Data Science Approach

Brian E. Perron; Bryan G. Victor; David R. Hodge; Christopher P. Salas-Wright; Michael G. Vaughn; Robert Joseph Taylor

doi:10.1177/1049731515624966

Laying the Foundations for Scientometric Research: A Data Science Approach

Brian E. Perron, Bryan G. Victor, David R. Hodge, Christopher P. Salas-Wright, Michael G. Vaughn, Robert Joseph Taylor

Graduate School of Social Welfare

Research output: Contribution to journal › Article › peer-review

20 Citations (Scopus)

Abstract

Objective: Scientometric studies of social work have stagnated due to problems with the organization and structure of the disciplinary literature. This study utilized data science to produce a set of research tools to overcome these methodological challenges. Method: We constructed a comprehensive list of social work journals for a 25-year time period and searched for all available article records using 35 different databases. Customized software was developed to restructure article records into a single analyzable database. We then computed the annual journal growth from the database. Results: A population of 90 disciplinary journals was established, and 33,330 article records were retrieved from 80 of these journals. Rapid and consistent growth in the number of social work journals was observed, particularly from 1997 up to 2005. Conclusions: The population list of social work journals, database of article records, and customized software builds the foundation for future scientometric studies in social work.

Original language	English
Pages (from-to)	802-812
Number of pages	11
Journal	Research on Social Work Practice
Volume	27
Issue number	7
DOIs	https://doi.org/10.1177/1049731515624966
Publication status	Published - 2017 Nov 1

Bibliographical note

Funding Information:
Families in Societya Social Work British Journal of Social Worka Journal of Gerontological Social Work Research On Social Work Practice Social Work in Health Care International Social Work Health & Social Work Journal of Social Work Education Journal of Sociology & Social Welfare Social Work Education Journal of Human Behavior in the Social Environment Clinical Social Work Journal Indian Journal of Social Work Maatskaplike Werk Affilia Child & Adolescent Social Work Journal Social Service Review Reflections: Narratives of Professional Helping Social Work With Groups Journal of Psychosocial Oncology Journal of Social Service Research Administration in Social Work Child & Family Social Work Social Work Researcha Journal of Social Work Practice Journal of Gay & Lesbian Social Services Journal of Teaching in Social Work Smith College Studies in Social Work Journal of Community Practice Journal of Technology in Human Servicesa European Journal of Social Work International Journal of Social Welfare Canadian Social Work Review Arete Journal of Social Work Practice in The Addictions Social Work & Christianity Journal of Baccalaureate Social Work Social Work in Mental Health Journal of Religion & Spirituality in Social Worka Qualitative Social Work Journal of Family Social Work Journal of Ethnic & Cultural Diversity in Social Worka Social Work in Public Health Journal of Hiv/Aids & Social Services Social Development Issues Psychoanalytic Social Worka Journal of Social Work Australian Social Work Children & Schoolsa Advances in Social Work Social Work Review Social Work & Social Sciences Review Social Work & Society Professional Development

Publisher Copyright:
© 2016, © The Author(s) 2016.

All Science Journal Classification (ASJC) codes

Social Sciences (miscellaneous)
Sociology and Political Science
Psychology(all)

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10.1177/1049731515624966

Cite this

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title = "Laying the Foundations for Scientometric Research: A Data Science Approach",

abstract = "Objective: Scientometric studies of social work have stagnated due to problems with the organization and structure of the disciplinary literature. This study utilized data science to produce a set of research tools to overcome these methodological challenges. Method: We constructed a comprehensive list of social work journals for a 25-year time period and searched for all available article records using 35 different databases. Customized software was developed to restructure article records into a single analyzable database. We then computed the annual journal growth from the database. Results: A population of 90 disciplinary journals was established, and 33,330 article records were retrieved from 80 of these journals. Rapid and consistent growth in the number of social work journals was observed, particularly from 1997 up to 2005. Conclusions: The population list of social work journals, database of article records, and customized software builds the foundation for future scientometric studies in social work.",

author = "Perron, {Brian E.} and Victor, {Bryan G.} and Hodge, {David R.} and Salas-Wright, {Christopher P.} and Vaughn, {Michael G.} and Taylor, {Robert Joseph}",

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Laying the Foundations for Scientometric Research: A Data Science Approach

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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