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• W4281735940 abstract "• The originality of papers is measured based knowledge units’ network, which is captured by the content of papers. • The content of papers is divided into three parts: research topics, research methods and research results by characteristic words and location in abstract. • Comparing with citations network analysis and knowledge combinations, the method is more reasonable and exact in measuring originality of academic papers. • The practical implication of our research is that to propose a new method to measure the originality of papers. Research on the evaluation of the quality of academic papers is attracting more attention from scholars in scientometrics. However, most previous researches have assessed paper quality based on external indicators, such as citations, which failed to account for the content of the research. To that end, this paper proposed a new method for measuring a paper's originality. The method was based on knowledge units in semantic networks, focusing on the relationship and semantic similarity of different knowledge units. Connectivity and path similarity between different content elements were used in particular networks as indicators of originality. This study used papers published between 2014 and 2018 in three categories (i.e. Library & Information Science, Educational Psychology, and Carbon Nanotubes) and divided their content into three parts (i.e. research topics, research methods and research results). It was found that the originality in all categories increase each year. Furthermore, a comparison of our new method with previous models of citation network analysis and knowledge combination analysis showed that our new method is better than those previous methods when used in measuring originality." @default.
• W4281735940 created "2022-06-13" @default.
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• W4281735940 date "2022-08-01" @default.
• W4281735940 modified "2023-10-16" @default.
• W4281735940 title "A new method for measuring the originality of academic articles based on knowledge units in semantic networks" @default.
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• W4281735940 doi "https://doi.org/10.1016/j.joi.2022.101306" @default.
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