论人类情感在时空中的习得

Julius Schöning, Corinna E. Bonhage
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引用次数: 4

摘要

情感评估通常在学术或医疗环境中进行。环境因素的影响,如地点的特征、天气或一天中的时间,对居民情绪状态的影响往往被忽视,因此情绪作为一种动态特征,不能用于城市规划或发展。为了将情感作为时空数据进行估计,越来越多的研究团体关注于从社交网络平台(如Twitter或Facebook)中提取情感。由此产生的情绪评估的质量和可靠性无法与直接的情绪评估相比,例如,由于社会群体中情绪陈述可能存在偏见。为了弥补这一差距,我们设计了一个基于网络的调查服务,允许在现实环境中获取一大批参与者的地理位置情感评级,这反过来又与许多环境变量相关。在本文中,我们介绍了这种基于web的服务的体系结构以及初步研究的结果。最后,我们讨论了时空情感数据的可能用例,基于web的服务的局限性,并对未来可能的项目进行了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Acquisition of Human Emotions in Space and Time
Emotion assessments traditionally take place in academic or medical settings. The impact of environmental factors such as e.g. the characteristics of the place, the weather, or the time of day on the emotional state of inhabitants are often dismissed, thus emotions as a dynamic feature cannot be used for city planning or development. To estimate emotions as spatio-temporal data, a growing research community focused on emotion extraction from social network platforms such as Twitter or Facebook. The quality and the reliability of the resulting emotion evaluations are not comparable to direct emotion assessments, e.g. because of possible biases of emotional statements in social communities. In order to bridge this gap, we designed a web-based survey service that allows for the acquisition of geo-located emotion ratings of a huge group of participants in real-world environments, which in turn can be related to numerous environmental variables. In this paper, we present the architecture of this web-based service along with first results of a pilot study. In the end, we discuss possible use cases for spatio-temporal emotion data, the limitations of our web-based service, and present an outlook on possible future projects.
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