Abstract
The meaning of a concept or a word changes over time. Such concept drift reects the change of the social consensus as well. Studying concept drift over time is valuable for researchers who are interested in language or culture evolution. Recent word embedding technologies inspire us to automatically detect concept drift in large-scale corpora. However, comparing embeddings generated from different corpora is a complex task. In this paper, we propose to use a simple approach for detecting concept drift based on the change in word contexts from different time periods and apply it to subsequent time periods so that the detailed drift could be detected and visualised. We dive into certain words to track how the meaning of a word changes gradually over a long time span with relevant historical events which demonstrates the effect of our method.
Original language | English |
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Pages (from-to) | 153-163 |
Number of pages | 11 |
Journal | CEUR workshop proceedings |
Volume | 2871 |
Publication status | Published - 2021 |
Event | 1st Workshop on AI + Informetrics, AII 2021 - Virtual, Online Duration: 17 Mar 2021 → 17 Mar 2021 Conference number: 1 |
Keywords
- Concept drifting
- Historical event
- Word context
- Word embedding