Literature DB >> 23924061

Similarities and differences of emotions in human-machine and human-human interactions: what kind of emotions are relevant for future companion systems?

Steffen Walter1, Cornelia Wendt, Jan Böhnke, Stephen Crawcour, Jun-Wen Tan, Andre Chan, Kerstin Limbrecht, Sascha Gruss, Harald C Traue.   

Abstract

Cognitive-technical intelligence is envisioned to be constantly available and capable of adapting to the user's emotions. However, the question is: what specific emotions should be reliably recognised by intelligent systems? Hence, in this study, we have attempted to identify similarities and differences of emotions between human-human (HHI) and human-machine interactions (HMI). We focused on what emotions in the experienced scenarios of HMI are retroactively reflected as compared with HHI. The sample consisted of N = 145 participants, who were divided into two groups. Positive and negative scenario descriptions of HMI and HHI were given by the first and second groups, respectively. Subsequently, the participants evaluated their respective scenarios with the help of 94 adjectives relating to emotions. The correlations between the occurrences of emotions in the HMI versus HHI were very high. The results do not support the statement that only a few emotions in HMI are relevant.

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Year:  2013        PMID: 23924061     DOI: 10.1080/00140139.2013.822566

Source DB:  PubMed          Journal:  Ergonomics        ISSN: 0014-0139            Impact factor:   2.778


  4 in total

1.  Human versus chatbot: Understanding the role of emotion in health marketing communication for vaccines.

Authors:  Wan-Hsiu Sunny Tsai; Di Lun; Nicholas Carcioppolo; Ching-Hua Chuan
Journal:  Psychol Mark       Date:  2021-07-27

2.  The Influence of Emotion on Keyboard Typing: An Experimental Study Using Auditory Stimuli.

Authors:  Po-Ming Lee; Wei-Hsuan Tsui; Tzu-Chien Hsiao
Journal:  PLoS One       Date:  2015-06-11       Impact factor: 3.240

3.  Two-Level Domain Adaptation Neural Network for EEG-Based Emotion Recognition.

Authors:  Guangcheng Bao; Ning Zhuang; Li Tong; Bin Yan; Jun Shu; Linyuan Wang; Ying Zeng; Zhichong Shen
Journal:  Front Hum Neurosci       Date:  2021-01-20       Impact factor: 3.169

4.  Affective Computing and the Impact of Gender and Age.

Authors:  Stefanie Rukavina; Sascha Gruss; Holger Hoffmann; Jun-Wen Tan; Steffen Walter; Harald C Traue
Journal:  PLoS One       Date:  2016-03-03       Impact factor: 3.240

  4 in total

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