German in Flux: Detecting Metaphoric Change via Word Entropy

Abstract

This paper explores the informationtheoretic measure entropy to detect metaphoric change, transferring ideas from hypernym detection to research on language change. We also build the first diachronic test set for German as a standard for metaphoric change annotation. Our model shows high performance, is unsupervised, language-independent and generalizable to other processes of semantic change.

Time-Out: Temporal Referencing for Robust Modeling of Lexical Semantic Change

“…Evaluation Due to a lack of proper evaluation methods and datasets, all papers above have performed different, non-comparable evaluations. Previous evaluation procedures mainly tackle a few words: case studies of individual words (Wijaya and Yeniterzi, 2011;Jatowt and Duh, 2014;Hamilton et al, 2016a), or a comparison between a few changing and semantically stable words (Lau et al, 2012;Schlechtweg et al, 2017). Other works focus on the post hoc evaluation of their respective models (Kulkarni et al, 2015;Eger and Mehler, 2016).…”

A Wind of Change: Detecting and Evaluating Lexical Semantic Change across Times and Domains

“…VH is based on Shannon's entropy (Shannon, 1948), which measures the unpredictability of w's co-occurrences (Schlechtweg et al, 2017). HD is defined as…”

“…In (i), semantic vector spaces, each word is represented as two vectors reflecting its co-occurrence statistics at different periods of time (Gulordava and Baroni, 2011;Kim et al, 2014;Xu and Kemp, 2015;Eger and Mehler, 2016;Hamilton et al, 2016a,b;Hellrich and Hahn, 2016;Rosenfeld and Erk, 2018). LSC is typically measured by the cosine distance (or some alternative metric) between the two vectors, or by differences in contextual dispersion between the two vectors (Kisselew et al, 2016;Schlechtweg et al, 2017). (ii) Diachronic topic models infer a probability distribution for each word over different word senses (or topics), which are in turn modeled as a distribution over words (Wang and McCallum, 2006;Bamman and Crane, 2011;Wijaya and Yeniterzi, 2011;Lau et al, 2012;Mihalcea and Nastase, 2012;Cook et al, 2014;Frermann and Lapata, 2016).…”

“…(i) includes case studies of individual words (Sagi et al, 2009;Jatowt and Duh, 2014;Hamilton et al, 2016a), stand-alone comparison of a few hand-selected words (Wijaya and Yeniterzi, 2011;Hamilton et al, 2016b;Del Tredici and Fernández, 2017), comparison of hand-selected changing vs. semantically stable words (Lau et al, 2012;Cook et al, 2014), and post-hoc evaluation of the predictions of the presented models (Cook and Stevenson, 2010;Kulkarni et al, 2015;Del Tredici et al, 2016;Eger and Mehler, 2016;Ferrari et al, 2017). Schlechtweg et al (2017) propose a small-scale annotation of diachronic metaphoric change.…”

Quantifying the dynamics of topical fluctuations in language

“…This research broadly falls into two categories. On the one hand, methods proposals and critiques accompanied by exploratory results (Dubossarsky et al, 2017;Frermann and Lapata, 2016;Gulordava and Baroni, 2011;Hamilton et al, 2016b;Jatowt and Duh, 2014;Kulkarni et al, 2015;Sagi et al, 2011;Schlechtweg et al, 2017;Wijaya and Yeniterzi, 2011). On the other, applications of these methods, usually with more specific linguistic questions in mind (Dautriche et al, 2016;Dubossarsky et al, 2016;Hamilton et al, 2016a;Perek, 2016;Rodda et al, 2016;Xu and Kemp, 2015).…”