Subjects: Library Science，Information Science >> Information Science submitted time 2024-04-18
Abstract： Purpose/Significance The aim is to construct a mutation index to measure the innovation of academic papers, providing a reference for improving the evaluation system of academic paper innovation. Method/Process A large language model (LLM), Mistral-openorca, is utilized to extract the research questions and methods from papers. The mutation index is constructed based on two dimensions: the similarity of research questions and methods to existing studies, and the extent to which they stimulate subsequent research. Result/Conclusion Papers with high innovation scores generally have a higher citation frequency; among the top 10 ranked papers by innovation, seven introduced original methods or tools, whereas papers in the bottom 10 ranked by innovation had more mature research topics and methods at the time of publication, with lower levels of innovation; the correlation coefficient between the innovation score of the papers and their citation frequency is 0.530, and empirical research results further confirm the effectiveness of the mutation index proposed in this paper in measuring the innovation of academic papers.
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Awaiting Review
Subjects: Library Science，Information Science >> Information Processing submitted time 2024-04-18
Abstract： Abstract: Purpose/Significance The paper constructs the index of the discipline diversity of the paper reference, and explores the relationship between the discipline diversity of the paper reference and the citations. Method/Process The reference discipline diversity measurement index was designed based on the Rao-Stirling diversity index, and 15 variables including the reference discipline diversity of the paper were taken as the independent variable, the citation of the paper as the dependent variable, and the journal rank as the control variable. The regression model was generated by fitting the ordinary least square method. This paper discusses the relationship between the subject diversity of the paper references and the citation frequency. Result/Conclusion The index of reference diversity constructed by this research can reflect the degree of multidisciplinary knowledge integration of the paper. The diversity of the reference disciplines positively affects the citation frequency of the paper. The stronger the diversity of the reference disciplines, the higher the citation of the paper.
Peer Review Status:Awaiting Review
Subjects: Library Science，Information Science >> Information Science submitted time 2023-04-01 Cooperative journals: 《图书情报工作》
Abstract： [Purpose/significance] This paper discusses the collaboration pattern of research teams in the artificial intelligence field, and compares the differences among research teams in different collaboration pattern.[Method/process] Taking the identified AI leading research team as the research object, and according to the number of scholars and the indicator value of social network indicator in the team, the core scholars in the team were identified, so as to divide the collaboration pattern of the AI research team, and analyze the teams with different collaboration pattern with examples. On this basis, the differences among the leading teams of different collaboration pattern were compared and analyzed from several dimensions of network structure characteristics, research performance and geographical distribution.[Result/conclusion] The cooperative patterns, of research teams in the field of artificial intelligence are divided into four types:single-core pattern, dual-core pattern, multi-core pattern and equilibrium pattern. Among them, the research teams of single-core pattern and dual-core pattern all perform well in the research dimension.
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