基于情绪相关事件上下文的隐含情绪分类方法研究

情绪分类是情绪分析研究中的一个基本任务,旨在对文本表达的情绪进行分类。目前,该任务是自然语言处理研究中的一个热点问题。已有的研究一般借助于情绪关键词(例如,“高兴”,“伤心”)来进行情绪分类。然而,在实际中,存在大量的没有情绪关键词但表达情绪的文本,我们称这类情绪表达为隐含情绪表达。该文关注隐含情绪分类方法研究,提出了基于情绪关联事件的隐含情绪分类方法,我们认为情绪的关联事件可以用于对情绪类别进行分类。具体实现中,我们首先采用情绪关键词获得句子群;然后,去除情绪关键词,将上下文作为关联事件表达文本;最后,利用上下文进行情绪分类。实验结果表明,以上下文进行的情绪分类结果达到了一定的性能,远远好于随机分类结果。这一结果为进一步隐含情绪分类提供了良好的基础。

Implicit Emotion Classification with the Context of Emotion Related Event

Emotion classification is one basic task in emotion analysis, which has been a hot research issue in the community of Natural Language Processing. Precious studies often leverage the emotion keywords (e.g., happy, sad) to do emotion classification. However, there exists some text that includes no emotion keywords but does express emotions. We refer to the emotion expression without emotion keywords as implicit emotion expression. In this paper, we focus on the classification task on implicit emotion expression and propose a classification method with related events. We think that the related events are important indicates of the emotion categories. First, we collect the sentence groups that contains emotion keywords; Then, we delete the keywords and regard the context as describing the emotion related events. Third, we use the context as the feature source to perform emotion classification. Empirical studies demonstrate that using the context yields a nice performance for implicit emotion classification. This result provide a good basic for the studies on implicit emotion classification.
Key wordsemotion related events; emotion classification; emotion keywords