Understanding the evolving academic landscape of library and information science through faculty hiring data

Yongjun Zhu, Erjia Yan, Min Song

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Using a 40-year (from 1975 to 2015) hiring dataset of 642 library and Information science (LIS) faculty members from 44 US universities, this research reveals the disciplinary characteristics of LIS through several key aspects including gender, rank, country, university, major, and research area. Results show that genders and ranks among LIS faculty members are evenly distributed; geographically, more than 90 % of LIS faculty members received doctoral degrees in the US; meanwhile, 60 % of LIS faculty received Ph.D. in LIS, followed by Computer Science and Education; in regards to research interests, Human–Computer interaction, Digital Librarianship, Knowledge Organization and Management, and Information Behavior are the most popular research areas among LIS faculty members. Through a series of dynamic analyses, this study shows that the educational background of LIS faculty members is becoming increasingly diverse; in addition, research areas such as Human–Computer interaction, Social Network Analysis, Services for Children and Youth, Information Literacy, Information Ethics and Policy, and Data and Text Mining, Natural Language Processing, Machine Learning have received an increasing popularity. Predictive analyses are performed to discover trends on majors and research areas. Results show that the growth rate of LIS faculty members is linearly distributed. In addition, among faculty member’s Ph.D. majors, the share of LIS is decreasing while that the share of Computer Science is growing; among faculty members’ research areas, the share of Human–Computer interaction is on the rise.

Original languageEnglish
Pages (from-to)1461-1478
Number of pages18
JournalScientometrics
Volume108
Issue number3
DOIs
Publication statusPublished - 2016 Sep 1

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Information science
hiring
information science
computer science
Computer science
interaction
research interest
university
gender
librarianship
Electric network analysis
network analysis
popularity
Learning systems
social network
Education
literacy
moral philosophy
organization

All Science Journal Classification (ASJC) codes

  • Social Sciences(all)
  • Computer Science Applications
  • Library and Information Sciences

Cite this

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Understanding the evolving academic landscape of library and information science through faculty hiring data. / Zhu, Yongjun; Yan, Erjia; Song, Min.

In: Scientometrics, Vol. 108, No. 3, 01.09.2016, p. 1461-1478.

Research output: Contribution to journalArticle

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