Brave New World: Uncovering Topical Dynamics in the ACL Anthology Reference Corpus Using Term Life Cycle Information
Anne-Kathrin Schumann · 2016
One of the main interests in the analysis of large document collections is to discover domains of discourse that are still actively developing, growing in interest and relevance, at a given point in time, and to distinguish them from those topics that are in stagnation or decline.The present paper describes a terminologically inspired approach to this kind of task.The inputs to the method are a corpus spanning several decades of research in computational linguistics and a set of single-word terms that frequently occur in that corpus.The diachronic development of these terms is modelled by means of term life cycle information, namely the parameters relative frequency and productivity.In a second step, k-means clustering is used to identify groups of terms with similar development patterns.The paper describes a mathematical approach to modelling term productivity and discusses what kind of information can be obtained from this measure.The results of the clustering experiment are promising and well motivate future research.