Novel computational algorithms to index lexical markers of psychological distancing and their relationship to emotion regulation efficacy over time.
Novel computational algorithms to index lexical markers of psychological distancing and their relationship to emotion regulation efficacy over time.
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DOI：
10.1007/s42761-021-00053-x
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发表时间：
2021-09
期刊：
影响因子：
--
通讯作者：
Denny, Bryan T.
中科院分区：
文献类型：
--
作者：
Shahane, Anoushka D.;Pham, Daniel C.;Lopez, Richard B.;Denny, Bryan T.
一个人通过语言运用客观或空间/时间上遥远的视角的程度，即，语言距离，以前已被证明与幸福呈正相关。我们试图进一步阐明随着时间的推移，语言和情感之间的关系，作为一个功能的子策略的心理距离的实施。在研究1中，我们开发了新的深度机器学习算法，以确定语言模式反映两种类型的心理距离的程度，即客观（OBJ）和空间/时间（FAR）距离。在研究2中，在一个基于表达性写作的纵向情绪调节训练任务中，参与者在5个会话中以三种方式之一观察消极或中性刺激时转录他们的想法：通过实施客观语言（客观组），通过实施空间/时间距离语言（远组），或通过自然反应。我们发现，OBJ和FAR算法显着预测目标组中基于任务的自我报告的负面影响的变化，并发现在远组中没有显着的关联。与远距离组相比，客观组的算法得分和自我报告的负面情绪之间的关系更强。这些发现描述了敏感的语言距离算法，能够跟踪自我报告的负面影响的变化。这些结果可能有助于开发利用自然语言处理的新型，不引人注目的情绪调节评估和干预措施。
The degree to which one employs an objective or spatially/temporally distant perspective via language, i.e., linguistic distancing, has previously been shown to be positively associated with well-being. We sought to further elucidate relationships among language and emotion over time as a function of the implementation of sub-tactics of psychological distancing. In Study 1, we developed novel deep machine learning algorithms to identify the degree to which linguistic patterns reflect two types of psychological distancing, namely objective (OBJ) and spatial/temporal (FAR) distancing. In Study 2, in an expressive writing-based longitudinal emotion regulation training task, participants transcribed their thoughts while viewing negative or neutral stimuli over 5 sessions in one of three ways: by implementing objective language (Objective group), by implementing spatially/temporally distant language (Far group), or by responding naturally. We found that the OBJ and FAR algorithms significantly predicted changes in task-based self-reported negative affect in the Objective group and found no significant associations in the Far group. The relationship between the algorithm scores and self-reported negative affect was stronger in the Objective group compared to the Far group. These findings describe sensitive linguistic distancing algorithms that are capable of tracking changes in self-reported negative affect. These results may be useful in developing novel, unobtrusive emotion regulation assessments and interventions that utilize natural language processing.
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