论文标题
操纵情绪以进行地面真理情绪分析
Manipulating emotions for ground truth emotion analysis
论文作者
论文摘要
文本数据被用作可以大规模研究人类认知的镜头。情绪分析等方法现在是计算社会科学家的标准工具包，但通常依赖于未知有效性的第三人称注释。作为替代方案，本文从实验行为研究中介绍了在线情感诱导技术，作为一种基于文本情感分析的方法。从随机分配到幸福，中立或悲伤的参与者那里收集了文本数据。这些发现支持情绪吸引程序。然后，我们检查了词典方法如何检索诱发的情绪。所有方法都会导致真实情感条件之间的统计差异。总体而言，通过基于文本的测量值捕获了情绪差异的最多三分之一。预验证的分类器在检测真实情绪方面表现不佳。本文以局限性和未来研究的建议结束。
Text data are being used as a lens through which human cognition can be studied at a large scale. Methods like emotion analysis are now in the standard toolkit of computational social scientists but typically rely on third-person annotation with unknown validity. As an alternative, this paper introduces online emotion induction techniques from experimental behavioural research as a method for text-based emotion analysis. Text data were collected from participants who were randomly allocated to a happy, neutral or sad condition. The findings support the mood induction procedure. We then examined how well lexicon approaches can retrieve the induced emotion. All approaches resulted in statistical differences between the true emotion conditions. Overall, only up to one-third of the variance in emotion was captured by text-based measurements. Pretrained classifiers performed poorly on detecting true emotions. The paper concludes with limitations and suggestions for future research.
