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| Exploring the Evolution of Research Topics Based on Partial-Cumulative Citation Co-Word Network with Word2Vec |
| Cheng Xiufeng, Zou Jingjing, Ye Guanghui, Xia Lixin |
| School of Information Management, Central China Normal University, Wuhan 430079 |
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Abstract Discovering and clarifying the development and evolution of disciplines contribute significantly to scientific research and academic development. Targeting the single-dimension issue in regular co-word analysis, this paper proposes a subject identification and evolution analysis method based on the citation co-word network, and considers the field of “information science” as an example for empirical research. This method defines the “citation co-occurrence” association through the citation relationship, and builds a keyword network with word embedding method. Subsequently, the community detection strategy is adopted to identify field subjects, while the second discrete analysis methods are also employed to analyze the structure and trend of the subjects. The subject evolution path and trend are visualized, the results showing that the network proposed presents better topic clustering and trending visualization effect than the regular co-word networks. Indeed, the aforementioned proves that this method is an effective supplement to co-word analysis.
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Received: 21 July 2022
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