We present a method for characterizing a research work in terms of its focus, domain of application, and techniques used. We show how tracing these aspects over time provides a novel measure of the influence of research communities on each other. We extract these characteristics by matching semantic extraction patterns, learned using bootstrapping, to the dependency trees of sentences in an article's abstract. We combine this information with pre-calculated article-to-community assignments to study the influence of a community on others in terms of techniques borrowed and the 'maturing' of some communities to solve other problems. As a case study, we show how the computational linguistics community and its sub-fields have changed over the years with respect to their foci, methods used, and domain problems. For instance, we show that part-of-speech tagging and parsing have increasingly been adopted as tools for solving problems in other domains. We also observe that speech recognition and probability theory have had the most seminal influence.
REF also studied the problem of extracting focus, techniques and the domain of research papers to identify the influence of research communities over each other.
Analyzing the Dynamics of Research by Extracting Key Aspects of Scientific Papers
IJCNLP
Computer Science