Temporal Word Analogies: Identifying Lexical Replacement with Diachronic Word Embeddings
|Title:||Temporal Word Analogies: Identifying Lexical Replacement with Diachronic Word Embeddings||Authors:||Szymanski, Terrence||Permanent link:||http://hdl.handle.net/10197/9166||Date:||4-Aug-2017||Online since:||2018-01-11T15:06:41Z||Abstract:||This paper introduces the concept of temporal word analogies: pairs of words which occupy the same semantic space at different points in time. One well-known property of word embeddings is that they are able to effectively model traditional word analogies ("word w1 is to word w2 as word w3 is to word w4") through vector addition. Here, I show that temporal word analogies ("word w1 at time ta is like word w2 at time tß") can effectively be modeled with diachronic word embeddings, provided that the independent embedding spaces from each time period are appropriately transformed into a common vector space. When applied to a diachronic corpus of news articles, this method is able to identify temporal word analogies such as "Ronald Reagan in 1987 is like Bill Clinton in 1997", or "Walkman in 1987 is like iPod in 2007".||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||Association for Computational Linguistics||Copyright (published version):||2017 Association for Computational Linguistics||Keywords:||Temporal word analogies; Vector space models||DOI:||10.18653/v1/P17-2071||Language:||en||Status of Item:||Peer reviewed||Is part of:||Barzilay, R., Kan MY. (eds.) Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)|
|Appears in Collections:||Insight Research Collection|
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