SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentiment
<p dir="ltr">Because word semantics can substantially change across communities and contexts, capturing domain-specific word semantics is an important challenge. Here, we propose SEMAXIS, a simple yet powerful framework to characterize word semantics using many semantic axes in wordv...
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| مؤلفون آخرون: | , |
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2018
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| _version_ | 1864513513035137024 |
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| author | Jisun An (10230800) |
| author2 | Haewoon Kwak (5747558) Yong-Yeol Ahn (220468) |
| author2_role | author author |
| author_facet | Jisun An (10230800) Haewoon Kwak (5747558) Yong-Yeol Ahn (220468) |
| author_role | author |
| dc.creator.none.fl_str_mv | Jisun An (10230800) Haewoon Kwak (5747558) Yong-Yeol Ahn (220468) |
| dc.date.none.fl_str_mv | 2018-01-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.18653/v1/p18-1228 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/conference_contribution/SemAxis_A_Lightweight_Framework_to_Characterize_Domain-Specific_Word_Semantics_Beyond_Sentiment/25921075 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Artificial intelligence Language, communication and culture Linguistics Word semantics Domain-specific SEMAXIS Semantic axes Word vector spaces Sentiment analysis |
| dc.title.none.fl_str_mv | SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentiment |
| dc.type.none.fl_str_mv | Text Conference contribution info:eu-repo/semantics/publishedVersion text conference object |
| description | <p dir="ltr">Because word semantics can substantially change across communities and contexts, capturing domain-specific word semantics is an important challenge. Here, we propose SEMAXIS, a simple yet powerful framework to characterize word semantics using many semantic axes in wordvector spaces beyond sentiment. We demonstrate that SEMAXIS can capture nuanced semantic representations in multiple online communities. We also show that, when the sentiment axis is examined, SEMAXIS outperforms the state-of-theart approaches in building domain-specific sentiment lexicons.</p><h2>Other Information</h2><p dir="ltr">Published in: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.18653/v1/p18-1228" target="_blank">https://dx.doi.org/10.18653/v1/p18-1228</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_15aeae69fc38b0959bbf630578234253 |
| identifier_str_mv | 10.18653/v1/p18-1228 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/25921075 |
| publishDate | 2018 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond SentimentJisun An (10230800)Haewoon Kwak (5747558)Yong-Yeol Ahn (220468)Information and computing sciencesArtificial intelligenceLanguage, communication and cultureLinguisticsWord semanticsDomain-specificSEMAXISSemantic axesWord vector spacesSentiment analysis<p dir="ltr">Because word semantics can substantially change across communities and contexts, capturing domain-specific word semantics is an important challenge. Here, we propose SEMAXIS, a simple yet powerful framework to characterize word semantics using many semantic axes in wordvector spaces beyond sentiment. We demonstrate that SEMAXIS can capture nuanced semantic representations in multiple online communities. We also show that, when the sentiment axis is examined, SEMAXIS outperforms the state-of-theart approaches in building domain-specific sentiment lexicons.</p><h2>Other Information</h2><p dir="ltr">Published in: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.18653/v1/p18-1228" target="_blank">https://dx.doi.org/10.18653/v1/p18-1228</a></p>2018-01-01T00:00:00ZTextConference contributioninfo:eu-repo/semantics/publishedVersiontextconference object10.18653/v1/p18-1228https://figshare.com/articles/conference_contribution/SemAxis_A_Lightweight_Framework_to_Characterize_Domain-Specific_Word_Semantics_Beyond_Sentiment/25921075CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/259210752018-01-01T00:00:00Z |
| spellingShingle | SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentiment Jisun An (10230800) Information and computing sciences Artificial intelligence Language, communication and culture Linguistics Word semantics Domain-specific SEMAXIS Semantic axes Word vector spaces Sentiment analysis |
| status_str | publishedVersion |
| title | SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentiment |
| title_full | SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentiment |
| title_fullStr | SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentiment |
| title_full_unstemmed | SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentiment |
| title_short | SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentiment |
| title_sort | SemAxis: A Lightweight Framework to Characterize Domain-Specific Word Semantics Beyond Sentiment |
| topic | Information and computing sciences Artificial intelligence Language, communication and culture Linguistics Word semantics Domain-specific SEMAXIS Semantic axes Word vector spaces Sentiment analysis |