Papers › Temporal Word Analogies: Identifying Lexical Replacement with Diachronic Word Embeddings
Temporal Word Analogies: Identifying Lexical Replacement with Diachronic Word Embeddings
Terrence Szymanski
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 t_α is like word w₂ at time tᵦ{''}) 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{''}.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections