With the recent developments in information technologies, natural language processing (NLP) practices have made tasks in many areas easier and more practical. Nowadays, especially when big data are used in most research, NLP provides fast and easy methods for processing these data. The purpose of this paper is to identify subfields of library and information science (LIS) where NLP can be used and to provide a guide based on bibliometrics and social network analyses for researchers who intend to study this subject.
Within the scope of this study, 6,607 publications, including NLP methods published in the field of LIS, are examined and visualized by social network analysis methods.
After evaluating the obtained results, the subject categories of publications, frequently used keywords in these publications and the relationships between these words are revealed. Finally, the core journals and articles are classified thematically for researchers working in the field of LIS and planning to apply NLP in their research.
The results of this paper draw a general framework for LIS field and guides researchers on new techniques that may be useful in the field.
This paper was supported in part by a research grant from the Turkish Scientific and Technological Research Center (115K440).
Taskin, Z. and Al, U. (2019), "Natural language processing applications in library and information science", Online Information Review, Vol. 43 No. 4, pp. 676-690. https://doi.org/10.1108/OIR-07-2018-0217Download as .RIS
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