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International Journal on Digital Libraries

, Volume 20, Issue 4, pp 369–389 | Cite as

Anatomy of scholarly information behavior patterns in the wake of academic social media platforms

  • Hamed AlhooriEmail author
  • Mohammed Samaka
  • Richard Furuta
  • Edward A. Fox
Article

Abstract

As more scholarly content is born digital or converted to a digital format, digital libraries are becoming increasingly vital to researchers seeking to leverage scholarly big data for scientific discovery. Although scholarly products are available in abundance—especially in environments created by the advent of social networking services—little is known about international scholarly information needs, information-seeking behavior, or information use. The purpose of this paper is to address these gaps via an in-depth analysis of the information needs and information-seeking behavior of researchers, both students and faculty, at two universities, one in the USA and the other in Qatar. Based on this analysis, the study identifies and describes new behavior patterns on the part of researchers as they engage in the information-seeking process. The analysis reveals that the use of academic social networks has notable effects on various scholarly activities. Further, this study identifies differences between students and faculty members in regard to their use of academic social networks, and it identifies differences between researchers according to discipline. Although the researchers who participated in the present study represent a range of disciplinary and cultural backgrounds, the study reports a number of similarities in terms of the researchers’ scholarly activities.

Keywords

Digital libraries Information needs Information-seeking behavior Information organization Scholarly communication Reference management Social media Academic social network Scholarly big data 

Notes

Acknowledgements

This publication was made possible by NPRP Grant # 4–029–1–007 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. This work was supported in part by the Office of Advanced Scientific Computing Research, Office of Science, US Department of Energy, under Contract DE-AC02–06CH11357. An earlier version of the initial work was presented at a TPDL conference [136] and an ICADL conference [137].

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceNorthern Illinois UniversityDeKalbUSA
  2. 2.Argonne National LaboratoryLemontUSA
  3. 3.Department of Computer Science and EngineeringQatar UniversityDohaQatar
  4. 4.Center for the Study of Digital Libraries and Department of Computer Science and EngineeringTexas A&M UniversityCollege StationUSA
  5. 5.Department of Computer ScienceVirginia TechBlacksburgUSA

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