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. 2021;126(2):1527-1551.
doi: 10.1007/s11192-020-03800-2. Epub 2020 Dec 17.

Forecasting the future of library and information science and its sub-fields

Zehra Taşkın  1
Affiliations

Forecasting the future of library and information science and its sub-fields

Zehra Taşkın. Scientometrics. 2021.

Abstract

Forecasting is one of the methods applied in many studies in the library and information science (LIS) field for numerous purposes, from making predictions of the next Nobel laureates to potential technological developments. This study sought to draw a picture for the future of the LIS field and its sub-fields by analysing 97 years of publication and citation patterns. The core Web of Science indexes were used as the data source, and 123,742 articles were examined in-depth for time series analysis. The social network analysis method was used for sub-field classification. The field was divided into four sub-fields: (1) librarianship and law librarianship, (2) health information in LIS, (3) scientometrics and information retrieval and (4) management and information systems. The results of the study show that the LIS sub-fields are completely different from each other in terms of their publication and citation patterns, and all the sub-fields have different dynamics. Furthermore, the number of publications, references and citations will increase significantly in the future. It is expected that more scholars will work together. The future subjects of the LIS field show astonishing diversity from fake news to predatory journals, open government, e-learning and electronic health records. However, the findings prove that publish or perish culture will shape the field. Therefore, it is important to go beyond numbers. It can only be achieved by understanding publication and citation patterns of the field and developing research policies accordingly.

Keywords: Disciplinary differences; Forecasting; Library and information science; Sub-field analysis; Time series analysis.

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Figures

Fig. 1
Fig. 1
Most used keywords of the time series analysis studies in LIS (The sunburst graph was created by using Flourish Studio (https://app.flourish.studio/). Keyword occurrences were calculated by using VOSviewer. Before the calculation, the keyword standardization process was conducted.)
Fig. 2
Fig. 2
The main characteristics of the dataset.
Fig. 3
Fig. 3
Clustering for journals in the dataset (networks of co-cited journals and keyword co-occurrence)
Fig. 4
Fig. 4
Distribution of journals into subject clusters
Fig. 5
Fig. 5
Forecasting for number of publications
Fig. 6
Fig. 6
Distribution of citations according to sub-fields
Fig. 7
Fig. 7
Forecasting for citations
Fig. 8
Fig. 8
Forecasting of the number of references
Fig. 9
Fig. 9
Forecasting of collaboration patterns
Fig. 10
Fig. 10
Forecasts by different periods
Fig. 11
Fig. 11
Emerging subjects of the LIS field (Flourish Studio was used to create the radial tree)
See this image and copyright information in PMC

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