Cascades, islands, or streams? Time, topic, and scholarly activities in humanities and social science research

本研究的目的是创建工具来分析跨异构语料库的主题生命周期。虽然大规模数据集的增长使科学数据集内部的检查成为可能，但缺乏跨数据集的研究-检查不同的科学活动如何促进或推动科学发现。该项目将研究四个领域的主题发展：科学史、社会网络分析、认知科学和数字人文科学。对这些领域中主题生命周期的考察应该能让我们深入了解社会科学和人文学科的学术是如何跨流派发展的。三角测量的方法（词分析，主题建模，突发检测和生存分析）将被用来确保最高水平的有效性。该项目在数据集组合方面具有创新性；这项研究将结合来自正式来源（论文、会议记录、期刊文章和拨款提案）和非正式沟通渠道（listservs、博客和twitter）的数据，以便为科学沟通提供更全面的视角。多年来，我们对学术景观的认识，以及随后对创新、生产力和影响的理解，在很大程度上都是由单一来源的数据提供的。然而，反映学术活动独特领域的多样化数据集的增长已经改变了研究格局，并为创造对科学本质更准确的理解提供了机会。这项工作的结果将对决策者产生影响，因为他们试图确定新兴的研究领域。它还将为确定新兴知识领域的某些沟通渠道的重要性提供一个指标——确定哪些学术活动最能代表新兴领域，从而确定不应再被边缘化的数据集，而应纳入我们对学术的理解和衡量。这项提议的主要广泛影响之一是通过利用印第安纳大学的学生使者计划培养新的研究人员，该计划将允许学生与私人顾问一起工作，前往参加会议，并有一个静修场所，他们将分享自己的研究并参与同伴指导。此外，该项目应该帮助学者和决策者了解新兴的研究领域以及传播和分享新知识的方法。这项拨款是“挖掘数据挑战”的一部分，这是一项国际竞赛，旨在促进各国之间的研究合作，并鼓励在社会科学和人文科学领域采用创新方法分析大型数据集。除美国研究团队外，该项目还包括来自加拿大和英国的研究人员。

The objective of this study is to create tools to allow for analysis of topic lifecycles across heterogeneous corpora. While the growth of large-scale datasets has enabled examination within scientific datasets, there is a lack of research that looks across datasets--examining how different scientific activities enable or propel scientific discovery. This project will examine the development of topics in four domains: history of science, social network analysis, cognitive science, and digital humanities. Examination of the lifecycle of topics in these domains should provide insights into how scholarship evolves across genres in the social sciences and humanities. Triangulation of the methods (word analysis, topic modeling, burst detection, and survival analysis) will be used to ensure the highest level of validity. This project is innovative in its combination of datasets; this research will combine data from formal sources (dissertations, conference proceedings, journal articles, and grant proposals) and informal communication channels (listservs, blogs, and twitter) in order to provide a more holistic lens on scientific communication. For years, our knowledge of the scholarly landscape, and subsequently, our understanding of innovation, productivity, and impact, has been largely informed by data from a single source. However, the growth of diverse datasets that reflect unique areas of scholarly activity have altered the research landscape and provide an opportunity to create more accurate understandings of the nature of science. The results of this work will have implications for policy makers, as they seek to identify emergent areas of research. It will also provide an indicator of the importance of certain communication channels for identifying emerging areas of knowledge--identifying which scholarly activities are most indicative of emerging areas and, thereby, identifying datasets that should no longer be marginalized, but built into our understandings and measurements of scholarship.One of the chief broader impacts of this proposal is the development of new researchers through the use of Indiana University's student emissary program, which will allow students to work alongside the PIs, travel to meetings, and have a retreat in which they will share their own research and engage in peer mentoring. Further, the project should help inform both scholars and policy makers about emergent areas of research and for ways of disseminating and sharing new knowledge.This grant was made as part of the Digging Into Data Challenge, an international competition designed to foster research collaboration across countries and to encourage innovative approaches to analyzing large data sets in the social sciences and humanities. In addition to the US research team, this project includes researchers from Canada and the United Kingdom.