{"id":479,"date":"2022-01-19T23:10:00","date_gmt":"2022-01-19T15:10:00","guid":{"rendered":"http:\/\/140.115.70.194:6417\/?p=479"},"modified":"2024-11-09T19:22:46","modified_gmt":"2024-11-09T11:22:46","slug":"share-onchinese-emobank-building-valence-arousal-resources-for-dimensional-sentiment-analysis-share-on","status":"publish","type":"post","link":"https:\/\/ainlp.tw\/index.php\/2022\/01\/19\/share-onchinese-emobank-building-valence-arousal-resources-for-dimensional-sentiment-analysis-share-on\/","title":{"rendered":"Chinese EmoBank: Building Valence-Arousal Resources for Dimensional Sentiment Analysis"},"content":{"rendered":"\n<p>Lung-Hao Lee, Jian-Hong Li, and Liang-Chih Yu*. <\/p>\n\n\n\n<p><em>ACM Transactions on Asian and Low-Resource Language Information Processing<\/em>\u00a0(<em><strong>ACM TALLIP<\/strong><\/em>), 21(4), Article 65, pages 1-18.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity is-style-wide\"\/>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p class=\"has-medium-font-size\"><strong>Abstract<\/strong><\/p>\n\n\n\n<p style=\"font-size:clamp(14px, 0.875rem + ((1vw - 3.2px) * 0.156), 16px);\">An increasing amount of research has recently focused on dimensional sentiment analysis that represents affective states as continuous numerical values on multiple dimensions, such as&nbsp;<strong>valence-arousal (VA)<\/strong>&nbsp;space. Compared to the categorical approach that represents affective states as distinct classes (e.g., positive and negative), the dimensional approach can provide more fine-grained (real-valued) sentiment analysis. However, dimensional sentiment resources with valence-arousal ratings are very rare, especially for the Chinese language. Therefore, this study aims to: (1) Build a Chinese valence-arousal resource called Chinese EmoBank, the first Chinese dimensional sentiment resource featuring various levels of text granularity including 5,512 single words, 2,998 multi-word phrases, 2,582 single sentences, and 2,969 multi-sentence texts. The valence-arousal ratings are annotated by crowdsourcing based on the&nbsp;<strong>Self-Assessment Manikin (SAM)<\/strong>&nbsp;rating scale. A corpus cleanup procedure is then performed to improve annotation quality by removing outlier ratings and improper texts. (2) Evaluate the proposed resource using different categories of classifiers such as lexicon-based, regression-based, and neural-network-based methods, and comparing their performance to a similar evaluation of an English dimensional sentiment resource.<\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<figure class=\"wp-block-image aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"789\" src=\"http:\/\/140.115.70.194:6417\/wp-content\/uploads\/2023\/12\/\u622a\u5716-2023-12-29-\u4e0b\u534811.15.10-1024x789.png\" alt=\"\" class=\"wp-image-481\" style=\"width:504px;height:auto\" srcset=\"https:\/\/ainlp.tw\/wp-content\/uploads\/2023\/12\/\u622a\u5716-2023-12-29-\u4e0b\u534811.15.10-1024x789.png 1024w, https:\/\/ainlp.tw\/wp-content\/uploads\/2023\/12\/\u622a\u5716-2023-12-29-\u4e0b\u534811.15.10-300x231.png 300w, https:\/\/ainlp.tw\/wp-content\/uploads\/2023\/12\/\u622a\u5716-2023-12-29-\u4e0b\u534811.15.10-768x592.png 768w, https:\/\/ainlp.tw\/wp-content\/uploads\/2023\/12\/\u622a\u5716-2023-12-29-\u4e0b\u534811.15.10.png 1168w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>Lung-Hao Lee, Jian-Hong Li, and Liang-Chih Yu*<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_themeisle_gutenberg_block_has_review":false,"footnotes":""},"categories":[6],"tags":[35,11,43],"class_list":["post-479","post","type-post","status-publish","format-standard","hentry","category-achievements","tag-35","tag-acm-tallip","tag-emotion"],"blocksy_meta":[],"_links":{"self":[{"href":"https:\/\/ainlp.tw\/index.php\/wp-json\/wp\/v2\/posts\/479","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ainlp.tw\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ainlp.tw\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ainlp.tw\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ainlp.tw\/index.php\/wp-json\/wp\/v2\/comments?post=479"}],"version-history":[{"count":5,"href":"https:\/\/ainlp.tw\/index.php\/wp-json\/wp\/v2\/posts\/479\/revisions"}],"predecessor-version":[{"id":795,"href":"https:\/\/ainlp.tw\/index.php\/wp-json\/wp\/v2\/posts\/479\/revisions\/795"}],"wp:attachment":[{"href":"https:\/\/ainlp.tw\/index.php\/wp-json\/wp\/v2\/media?parent=479"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ainlp.tw\/index.php\/wp-json\/wp\/v2\/categories?post=479"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ainlp.tw\/index.php\/wp-json\/wp\/v2\/tags?post=479"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}