新颖性
引用
计算机科学
数据科学
科学文献
度量(数据仓库)
科学知识社会学
认识论
科学网
心理学
认知科学
政治学
社会心理学
万维网
数据挖掘
梅德林
哲学
古生物学
法学
生物
作者
Erin Leahey,Jina Lee,Russell J. Funk
标识
DOI:10.1177/00031224231168074
摘要
Novelty and impact are key characteristics of the scientific enterprise. Classic theories of scientific change distinguish among different types of novelty and emphasize how a new idea interacts with previous work and influences future flows of knowledge. However, even recently developed measures of novelty remain unidimensional, and continued reliance on citation counts captures only the amount, but not the nature, of scientific impact. To better align theoretical and empirical work, we attend to different types of novelty (new results, new theories, and new methods) and whether a scientific offering has a consolidating form of influence (bringing renewed attention to foundational ideas) or a disruptive one (prompting subsequent scholars to overlook them). By integrating data from the Web of Science (to measure the nature of influence) with essays written by authors of Citation Classics (to measure novelty type), and by joining computational text analysis with statistical analyses, we demonstrate clear and robust patterns between type of novelty and the nature of scientific influence. As expected, new methods tend to be more disruptive, whereas new theories tend to be less disruptive. Surprisingly, new results do not have a robust effect on the nature of scientific influence.
科研通智能强力驱动
Strongly Powered by AbleSci AI