论文标题
自然语言处理，用于情绪的认知分析
Natural Language Processing for Cognitive Analysis of Emotions
论文作者
论文摘要
文本中的情感分析有两个主要局限性：带注释的金标准语料库大多是小而均匀的，并且情感识别通常被简化为句子级别的分类问题。为了解决这些问题，我们介绍了一种新的注释方案，以探索情绪及其原因，以及一个新的法国数据集，该数据集由情感场景的自传说明组成。通过应用A. Finkel开发的情绪的认知分析来帮助人们改善情绪管理，从而收集了文本。该方法需要通过接受认知分析的教练对情感事件进行手动分析。我们提出了一种基于规则的方法，以自动注释情绪及其语义角色（例如情感原因），以促进教练对相关方面的识别。我们使用图形结构研究了未来的情绪分析方向。
Emotion analysis in texts suffers from two major limitations: annotated gold-standard corpora are mostly small and homogeneous, and emotion identification is often simplified as a sentence-level classification problem. To address these issues, we introduce a new annotation scheme for exploring emotions and their causes, along with a new French dataset composed of autobiographical accounts of an emotional scene. The texts were collected by applying the Cognitive Analysis of Emotions developed by A. Finkel to help people improve on their emotion management. The method requires the manual analysis of an emotional event by a coach trained in Cognitive Analysis. We present a rule-based approach to automatically annotate emotions and their semantic roles (e.g. emotion causes) to facilitate the identification of relevant aspects by the coach. We investigate future directions for emotion analysis using graph structures.
