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Detecting Research Frontiers Based on Twitter |
Wuxihong Jiangbulati1,2,Wang Xiaomei1( ),Chen Ting1,3,4 |
1Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China 2School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China 3National Science Library, Chinese Academy of Sciences, Beijing 100190, China 4Department of Library, Information and Archives Management, University of Chinese Academy of Sciences, Beijing 100190, China |
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Abstract [Objective] This paper designs a Twitter-based method to identify emerging research topics, aiming to identify the latest developments of a specific discipline. [Methods] First, we analyzed the principles and practices of using Twitter to identify research topics. Then, we proposed a monitoring index system based on the influence of scholars and contents. Third, we conducted an empirical analysis in the field of natural language processing (NLP). [Results] The detection model is able to identify emerging research topics in NLP in a timely manner. Compared with reports on NLP status quo, 8 of the 13 research frontiers were successfully identified. [Limitations] Due to the open nature of social media, it is difficult to completely avoid subject-independent noise contents during dataset construction. [Conclusions] The proposed method is based on the scholarly UGC contents on Twitter, which is a feasible and effective way to detect the research frontiers of the discipline in a timely and forward-looking way.
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Received: 13 February 2022
Published: 16 February 2023
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Fund:Project of Literature and Information Capacity Building, Chinese Academy of Sciences(GHJ-QBZX-2021-04) |
Corresponding Authors:
Wang Xiaomei,ORCID:0000-0002-9895-1511,E-mail: wangxm@casisd.cn。
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