Abstract：Natural language processing applications in library and information science Purpose With the recent developments in information technologiesnatural language processingNLPpractices have made tasks in many areas easier and more practicalNowadaysespecially when big data are used in most researchNLP provides fast and easy methods for processing these dataThe purpose of this paper is to identify subfields of library and information scienceLISwhere NLP can be used and to provide a guide based on bibliometrics and social network analyses for researchers who intend to study this subjectDesignmethodologyapproach Within the scope of this study6607 publicationsincluding NLP methods published in the field of LISare examined and visualized by social network analysis methodsFindings After evaluating the obtained resultsthe subject categories of publicationsfrequently used keywords in these publications and the relationships between these words are revealedFinallythe core journals and articles are classified thematically for researchers working in the field of LIS and planning to apply NLP in their researchOriginalityvalue The results of this paper draw a general framework for LIS field and guides researchers on new techniques that may be useful in the fieldLibrary AutomationNLP can automatically process and analyze a large amount of informationConsulting ServiceBy analyzing the literatureyou can provide suggestions on how to apply NLP in the field of LISRetrieval and IndexingNLP can optimize the retrieval and index of resourcesespecially when processing big dataCollection classificationThrough the NLP methodresearchers can classify and organize data more quickly and easilyInstificational CollectionNLP can help researchers manage and organize information and information more effectivelyThis article is mainly concentrated in the application of natural language processingNLPin the field of library and information scienceLISIt tries to identify the Lis sub-field of NLPand provides guidelines for researchers intending to study this theme based on literature measuring and social network analysis