Using Machine Learning and Natural Language Processing to Analyze Library Chat Reference Transcripts

Abstract

The use of artificial intelligence and machine learning has rapidly become a standard technology across all industries and businesses for gaining insight and predicting the future. In recent years, the library community has begun looking at ways to improve library services by applying AI and machine learning techniques to library data. Chat reference in libraries generates a large amount of data in the form of transcripts. This study uses machine learning and natural language processing methods to analyze one academic library’s chat transcripts over a period of eight years. The built machine learning model tries to classify chat questions into a category of reference or nonreference questions. The purpose is to predict the category of future questions by the model with the hope that incoming questions can be channeled to appropriate library departments or staff.

Teen-adult interactions during the co-design of data literacy activities for the public library: insights from a natural language processing analysis of linguistic patterns

“…Although NLP tools have shown to be useful for information practitioners in the field (see, e.g. Lee et al , 2018; Ozeran and Martin, 2019; Papachristopoulos et al , 2019; Wang, 2022), will educators and librarians designing learning experiences apply such methods in situ? Awareness and training will be key.…”

“…Other recent examples of the use of NLP tools in the field of information science include the analysis of text data from reference chat transcripts with the goal of categorizing the types of questions asked by library patrons to predict future questions, more efficiently channeling questions to appropriate library staff, and informing library staff about a need for further support and guidance (Wang, 2022; Ozeran and Martin, 2019).…”

Reference Chatbots in Canadian Academic Libraries

“…Topics such as the use of AI to analyze transcripts of communication between librarians and users have been examined. 17 With recent advances in NLP, such as the launch of ChatGPT, which could have enormous impacts on education overall, it is a good time to shift focus from theorizing about the effects of chatbots in library spaces and begin assessing their use and impact. 18 This is especially important given the significant professional and ethical implications these technologies may have for academic librarianship.…”

Explicit Knowledge Database Interface Model System Based on Natural Language Processing Techniques and Immersive Technologies

“…Repositories and libraries have accumulated a significant amount of data in the form of chat transcripts. Analyzing the content of these transcripts can help library officials understand user information needs, allocate library resources more efficiently, and improve the quality of chat reference services [3].…”

“…For [2], an important activity of the organizations is the integration of individual knowledge into collective knowledge. Today, there is a need to properly manage tacit and explicit business knowledge [3], which, in the latter case, may be document-based, having a direct relationship with the productivity of the workforce and the efficiency of the organization. In many organizations, much of the business documents are not structured and do not have an adequate management system.…”