Semantic word shifts in a scientific domain |
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Authors: | Baitong Chen Ying Ding Feicheng Ma |
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Affiliation: | 1.Shanghai University,Shanghai,China;2.Indiana University,Bloomington,USA;3.Wuhan University,Wuhan,China;4.Tianjin Normal University,Tianjin,China |
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Abstract: | Understanding semantic word shifts in scientific domains is essential for facilitating interdisciplinary communication. Using a data set of published papers in the field of information retrieval (IR), this paper studies the semantic shifts of words in IR based on mining per-word topic distribution over time. We propose that semantic word shifts not only occur over time, but also over topics. The shifts are examined from two perspectives, the topic-level and the context-level. According to the over-time word-topic distribution, stable words and unstable words are recognized. The diverging and converging trends in the unstable type reveal characteristics of the topic evolution process. The context-level shifts are further detected by similarities between word vectors. Our work associates semantic word shifts with the evolving of topics, which facilitates a better understanding of semantic word shifts from both topics and contexts. |
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