Measuring interdisciplinary interactions using citation analysis and semantic analysis

Lu Huang, Xingxing Ni, Xiang Chen*, Yi Zhang

*Corresponding author for this work

    Research output: Contribution to journalConference articlepeer-review

    Abstract

    Interdisciplinary interactions and integrations have become a major feature of the current development of science and technology. How to measure the strength of interdisciplinary interactions between two disciplines is a crucial issue. In our study, we propose a novel measurement framework based on both citation analytics and semantic analytics, which integrates three indicators - direct citation, bibliographic coupling and research content. Especially, LDA model is incorporated with a word embedding model to create a semantic solution that effectively constructing discipline-keyword vectors based on bibliometric data. At last, entropy method is applied with these three indicators to assess the interdisciplinary interactions strength. The interactions between information science & library science and other six subjects are analyzed as the case study to demonstrate the reliability of the methodology, with subsequent empirical validations.

    Original languageEnglish
    Pages (from-to)140-152
    Number of pages13
    JournalCEUR Workshop Proceedings
    Volume2871
    Publication statusPublished - 2021
    Event1st Workshop on AI + Informetrics, AII 2021 - Virtual, Online
    Duration: 17 Mar 2021 → …

    Keywords

    • Citation analysis
    • Interdisciplinary interactions
    • Semantic analysis
    • Word embedding

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