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Exploiting the Unique Expression for Improved Sentiment ...
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由 K Sun 著作2021被引用 15 次 — Sentiment analysis on software engineering (SE) texts has been widely used in the SE research, such as evaluating app reviews or analyzing ...
Exploiting the Unique Expression for Improved Sentiment ...
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由 K Sun 著作2021被引用 15 次 — In this paper, we propose to improve sentiment analysis in SE texts by using sentence structures, a different perspective from building a domain dictionary.
Exploiting the Unique Expression for Improved Sentiment ...
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2024年9月13日 — Sentiment analysis on software engineering (SE) texts has been widely used in the SE research, such as evaluating app reviews or analyzing ...
Exploiting the Unique Expression for Improved Sentiment ...
arXiv
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arXiv
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由 K Sun 著作2021被引用 15 次 — Sentiment analysis is the study of the subjectivity and polarity of a manually-written text (usually identified as positive, neutral, or negative) [1]. Modern ...
Exploiting the Unique Expression for Improved Sentiment ...
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2021年3月24日 — This paper uses sentence structures to first identify whether the author is expressing her sentiment in a given clause of an SE text, ...
Exploiting the Unique Expression for Improved Sentiment ...
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Sun et al. [17] proposed sentence structure to improve sentiment analysis in software engineering text. Biswas et al. [18] in 2020, investigated the ...
Hongyu Kuang - Google 学术搜索
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... Software Maintenance (ICSM), 181-190, 2012. 22, 2012. Exploiting the unique expression for improved sentiment analysis in software engineering text. K Sun, H ...
[PDF] SentiStrength-SE: Exploiting domain specificity for ...
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Emotional emojis are employed as noisy labels of sentiments and a representation learning approach is proposed that uses both Tweets and GitHub posts ...
Analysis of Factors Influencing Developers' Sent…
Biblioteka Nauki
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Biblioteka Nauki
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Ma, G. Rong et al., “Exploiting the unique expression for improved sentiment analysis in software engineering text,” arXiv preprint arXiv:2103.13154, 2021.
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Hui Gao
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Co-authors ; Exploiting the unique expression for improved sentiment analysis in software engineering text. K Sun, H Gao, H Kuang, X Ma, G Rong, D Shao, H Zhang.
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