Developing a scholar classification scheme from publication patterns in academic science: A cluster analysis approach

Abstract

The impact of university rankings has driven scholars to increase productivity, and expanding collaboration has dramatically changed the publishing patterns in the academic publication system. The aim of this study was to develop a scholar classification scheme from publication patterns in academic science. Classification schemes are ways of describing groups that display different clusters of behaviors, approaches, or perspectives, and useful in the development of typologies. In this research, sample data are selected from three representative universities, considered a leading university, a middle-tier university, and a noncomprehensive university. A final set of 11,427 effective scholars and their 284,128 journal publication records were used to develop the classification scheme via cluster analysis. The results identify six types of scholars, labeled as: singleton (8%), small-team low performer (16%), smallteam high performer (17%), big-team strategist (22%), free-style follower (21%), and life-time warrior (17%). These six scholar types demonstrate different approaches to publishing that can be used to understand both individual and research team performance across different institutional settings. Additionally, possible future work was identified that uses the scholar classification scheme to define the behavior for agents in an agent-based model to simulate the strategicbehavior-driven academic publication system.

University Rankings and Goals: A Cluster Analysis

“…Scholars would benefit from the publications and subsequently citations as this would help in receiving recognition, promotions and esteem from the academic community. Universities focus on academic publications and citations as it helps in gaining more opportunities as funding and opportunities for future research (Gu and Blackmore 2019;Fox 1983;Sullivan 1996).…”

“…Higher education institutions have set public criteria for scholars (Gu and Blackmore 2019;Sullivan 1996). Accordingly, this study advises universities that have in their goals to have more citations and grow the research and join the first cluster, to set public criteria for the scholars.…”

On the Second Mission of Higher Education Institutions: The Case of ‘Polytechnics’ in Europe

“…Furthermore, it will favor disciplines that are inherently more productive. Researchers in life sciences, medical sciences and engineering tend to publish more frequently than those in mathematics and business, whereas those in social sciences and in humanities have a tendency to publish less frequently (Gu & Blackmore, 2019). The volume of publications also depends on the collaborative habits.…”

Enhance Arabic Clustering using an Educated Text Stemmer with WordNet as Extraction and Water Cycle Cluster

“…Besides, recent changes include the adoption of certain parts of a sentence for the English language, such as nouns [8]. For instance, English thesauruses have been comprehensively implemented for an enhanced text clustering quality [9][10][11][12][13][14][15][16][17][18]. The verbs and nouns used in sentences are particularly crucial in differentiating between diffrent groups, that Romanian people have explained precisely the denotation of 'crime' through the two notions of ''actus-reus' (awful or harmful 'verbs') and 'mens-rea' (bad or awful intention 'nouns') [19].…”