Diachronic Variation of Temporal Expressions in Scientific Writing Through the Lens of Relative Entropy

Abstract

Abstract. The abundance of temporal information in documents has lead to an increased interest in processing such information in the NLP community by considering temporal expressions. Besides domainadaptation, acquiring knowledge on variation of temporal expressions according to time is relevant for improvement in automatic processing. So far, frequency-based accounts dominate in the investigation of specific temporal expressions. We present an approach to investigate diachronic changes of temporal expressions based on relative entropy -with the advantage of using conditioned probabilities rather than mere frequency. While we focus on scientific writing, our approach is generalizable to other domains and interesting not only in the field of NLP, but also in humanities.

Registerial Adaptation vs. Innovation Across Situational Contexts: 18th Century Women in Transition

“…For example, Hughes et al ( 2012 ) measure stylistic influence in the evolution of literature, Klingenstein et al ( 2014 ) analyze language use in criminal trials, Bochkarev et al ( 2014 ) use KLD comparing word distributions within and across languages, Pechenick et al ( 2015 ) analyze cultural and linguistic evolution, and Fankhauser et al ( 2014 ) demonstrate the applicability of KLD for corpus comparison at large. In our own work, we have used KLD to analyze the linguistic development of English scientific writing over time 1 (Degaetano-Ortlieb and Teich, 2016 ; Degaetano-Ortlieb and Strötgen, 2018 ; Degaetano-Ortlieb et al, 2019b ), to investigate intra-textual variation across sections of research papers from genetics (Degaetano-Ortlieb and Teich, 2017 ), to analyze scientifization effects in literary studies (Degaetano-Ortlieb and Piper, 2019 ), to detect typical features of history texts (Degaetano-Ortlieb et al, 2019c ), and to investigate gender- and class-specific changes in court proceedings of the Old Bailey Court (Degaetano-Ortlieb, 2018 ).…”

Comparative Analysis of Preference in Contemporary and Earlier Texts Using Entropy Measures

“…Refs. [ 7 , 43 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 ] are cited in the Supplementary Materials.…”

Time expression and named entity analysis and recognition

“…and Gertz analyze time expressions in the texts from colloquial short message service (SMS) and scientific biomedical documents [201] while Degaetano-Ortlieb and Strotgen analyze time expressions in the scientific literature and their diachronic variation over a time span of about 350 years [47]. Tabassum et al analyze time expressions in the tweets which are informal text [208].…”