计算机科学 ›› 2020, Vol. 47 ›› Issue (10): 222-227.doi: 10.11896/jsjkx.190900173
王启发, 王中卿, 李寿山, 周国栋
WANG Qi-fa, WANG Zhong-qing, LI Shou-shan, ZHOU Guo-dong
摘要： 目前,新闻评论已成为新闻的重要衍生数据,新闻评论表达了评论者对新闻事件的观点、立场及个人情感,通过对新闻评论的情感倾向性分析有助于了解社会舆情及动向,因此,新闻评论的情感研究备受广大学者的青睐。通常的新闻评论情感分析只考虑评论文本自身的信息,而新闻评论文本信息和新闻正文信息往往是紧密相关的,基于此,文中提出一种基于交叉注意力机制并结合正文的新闻评论情感分类方法。首先通过双向长短时记忆网络模型分别对新闻正文与评论文本进行特征表示;然后基于交叉注意力机制进一步捕获评论与正文的关系,得到两个更新后的新闻正文与评论文本的向量表示;再将两者拼接得到的语义表示输入全连接层,使用sigmoid激活函数进行分类预测,从而实现新闻评论的情感分类。结果表明,提出的基于交叉注意力机制和新闻正文的评论情感分类模型可以有效地提升新闻评论情感分类的准确率,该模型的F1值较3个基准模型分别提高了1.72%,3.24%和6.21%。
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