Measuring the novelty of scientific publications: A fastText and local outlier factor approach |
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| Institution: | 1. School of Business Administration, Ulsan National Institute of Science and Technology, 50 UNIST-Gil, Ulsan 44919, Republic of Korea;2. School of Business Administration, Ajou University, 206 World cup-ro Yeongtong-gu, Suwon 16499, Republic of Korea;3. Department of Public Administration, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea |
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| Abstract: | Although the novelty of scientific publications has been the subject of previous studies, most have examined the distribution of references in the bibliography, which may not be effective in capturing implied scientific knowledge. We propose an analytical framework for measuring the novelty of scientific publications using a paper's title. At the heart of the framework, fastText is used to construct a vector space model in which papers with similar scientific knowledge are located close to each other, and the local outlier factor is used to measure the novelty of scientific knowledge implied in the papers on a numerical scale. The feasibility and validity of the analytical framework were assessed by comparing the average novelty scores of papers recommended with novelty-related tags in Faculty Opinions to those of papers without such tags. This case study of 15,653 papers published in a biomedical journal confirms that our framework is a useful complementary tool for the continuous assessment of the novelty of scientific publications and can serve as a starting point for developing more general models. |
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