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Predicting the Rise and Fall of Scientific Topics from Trends in their Rhetorical Framing

机译:从修辞框架的趋势预测科学主题的兴衰

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Computationally modeling the evolution of science by tracking how scientific topics rise and fall over time has important implications for research funding and public policy. However, little is known about the mechanisms underlying topic growth and decline. We investigate the role of rhetorical framing: whether the rhetorical role or function that authors ascribe to topics (as methods, as goals, as results, etc.) relates to the historical trajectory of the topics. We train topic models and a rhetorical function classifier to map topic models onto their rhetorical roles in 2.4 million abstracts from the Web of Science from 1991-2010. We find that a topic's rhetorical function is highly predictive of its eventual growth or decline. For example, topics that are rhetorically described as results tend to be in decline, while topics that function as methods tend to be in early phases of growth.
机译:通过跟踪科学主题随时间的上升和下降的方式,对科学的发展进行计算建模对研究经费和公共政策具有重要意义。但是,对于主题增长和下降的潜在机制知之甚少。我们研究了修辞框架的作用:作者归于主题的修辞作用或功能(作为方法,目标,结果等)是否与主题的历史轨迹有关。我们训练主题模型和修辞功能分类器,以将主题模型映射到1991-2010年间来自Web of Science的240万个摘要中的修辞作用。我们发现,主题的修辞功能可以高度预测其最终的增长或下降。例如,从口头上说是结果的主题趋于下降,而作为方法发挥作用的主题则处于增长的早期阶段。

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