On the Linearity of Semantic Change: Investigating Meaning Variation via Dynamic Graph Models

We consider two graph models of semantic change. The first is a time-series model that relates embedding vectors from one time period to embedding vectors of previous time periods. In the second, we construct one graph for each word: nodes in this graph correspond to time points and edge weights to the similarity of the word's meaning across two time points. We apply our two models to corpora across three different languages. We find that semantic change is linear in two senses. Firstly, today's embedding vectors (= meaning) of words can be derived as linear combinations of embedding vectors of their neighbors in previous time periods. Secondly, self-similarity of words decays linearly in time. We consider both findings as new laws/hypotheses of semantic change.Comment: Published at ACL 2016, Berlin (short papers

Language classification from bilingual word embedding graphs

We study the role of the second language in bilingual word embeddings in monolingual semantic evaluation tasks. We find strongly and weakly positive correlations between down-stream task performance and second language similarity to the target language. Additionally, we show how bilingual word embeddings can be employed for the task of semantic language classification and that joint semantic spaces vary in meaningful ways across second languages. Our results support the hypothesis that semantic language similarity is influenced by both structural similarity as well as geography/contact.Comment: To be published at Coling 201

A Short Note on Social-Semiotic Networks from the Point of View of Quantitative Semantics

In this extended abstract we discuss four related characteristics of semantic spaces as the standard model of meaning representation in quantitative semantics. We argue that these characteristics are challenged from the point of view of social web communities and the possibilities which they offer in terms of exploring semantic emph{and} pragmatic data. More specifically, we plead for a reconstruction of the weak contextual hypothesis in order to account for non-linguistic, pragmatic aspects of context. Finally, we mention two consequences of such a pragmatic turn, that is, in the area of named entity recognition and of language evolution