Emoji embedded representation based on emotion distribution
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原文链接
NETL
NSTL
万方数据
提出了一种基于情感分布的 emoji 嵌入式表示方法(emoji embedded representation based on emotion distribution,EDEER).EDEER方法采用基于BERT的情绪预测模型软标签,从真实数据中学习emoji嵌入式表示,通过情感分布直接建模emoji在各种情绪上的表达程度,使嵌入式表示中包含emoji的多种情感信息.在包含emoji的中文微博数据集上的多组对比实验表明,本文提出的方法可以有效地学习到与细粒度情绪直接关联的emoji嵌入式表示,构建具有较高情绪表达质量的emoji表示空间.
This paper proposes an emoji embedded representation based on emotion distribution(EDEER)method.The EDEER method adopts the soft label of BERT-based emotion prediction model to learn emoji embedded representation from real data,and directly models the expression degree of emoji on various sentiments through emotion distribution,so that the embedded representa-tion contains various emotional information of emoji.Multiple sets of comparative experiments on the Chinese Weibo dataset contai-ning emoji shows that the method proposed in this paper can effectively learn emoji embedded representations that are directly related to fine-grained sentiments,and build an emoji representation space with high emotional expression quality.
emojisentiment analysisembedded representationemotion distribution
NETL
NSTL
万方数据
