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        <title>Implicit Subjective and Sentimental Usages in Multi-sense Word Embeddings</title>
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        <namePart type="given">Yuqi</namePart>
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    <abstract>In multi-sense word embeddings, contextual variations in corpus may cause a univocal word to be embedded into different sense vectors. Shi et al. (2016) show that this kind of pseudo multi-senses can be eliminated by linear transformations. In this paper, we show that pseudo multi-senses may come from a uniform and meaningful phenomenon such as subjective and sentimental usage, though they are seemingly redundant. In this paper, we present an unsupervised algorithm to find a linear transformation which can minimize the transformed distance of a group of sense pairs. The major shrinking direction of this transformation is found to be related with subjective shift. Therefore, we can not only eliminate pseudo multi-senses in multisense embeddings, but also identify these subjective senses and tag the subjective and sentimental usage of words in the corpus automatically.</abstract>
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%0 Conference Proceedings
%T Implicit Subjective and Sentimental Usages in Multi-sense Word Embeddings
%A Sun, Yuqi
%A Shi, Haoyue
%A Hu, Junfeng
%Y Balahur, Alexandra
%Y Mohammad, Saif M.
%Y Hoste, Veronique
%Y Klinger, Roman
%S Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
%D 2018
%8 October
%I Association for Computational Linguistics
%C Brussels, Belgium
%F sun-etal-2018-implicit
%X In multi-sense word embeddings, contextual variations in corpus may cause a univocal word to be embedded into different sense vectors. Shi et al. (2016) show that this kind of pseudo multi-senses can be eliminated by linear transformations. In this paper, we show that pseudo multi-senses may come from a uniform and meaningful phenomenon such as subjective and sentimental usage, though they are seemingly redundant. In this paper, we present an unsupervised algorithm to find a linear transformation which can minimize the transformed distance of a group of sense pairs. The major shrinking direction of this transformation is found to be related with subjective shift. Therefore, we can not only eliminate pseudo multi-senses in multisense embeddings, but also identify these subjective senses and tag the subjective and sentimental usage of words in the corpus automatically.
%R 10.18653/v1/W18-6203
%U https://aclanthology.org/W18-6203
%U https://doi.org/10.18653/v1/W18-6203
%P 8-13

Markdown (Informal)

[Implicit Subjective and Sentimental Usages in Multi-sense Word Embeddings](https://aclanthology.org/W18-6203) (Sun et al., WASSA 2018)

• Implicit Subjective and Sentimental Usages in Multi-sense Word Embeddings (Sun et al., WASSA 2018)

ACL

• Yuqi Sun, Haoyue Shi, and Junfeng Hu. 2018. Implicit Subjective and Sentimental Usages in Multi-sense Word Embeddings. In Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 8–13, Brussels, Belgium. Association for Computational Linguistics.