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      Can a Virtual Agent provide good Emotional Support?


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      Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)

      Human Computer Interaction Conference

      4 - 6 July 2018

      HCI, Virtual agents, carers, affective computing, emotional support, personality, eHealth

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          In this study we explore whether an emotional support message sent to an informal carer by a Virtual Agent provides good quality emotional support, compared to the same message sent by a friend or sister with whom they have either a close, medium, or distant relationship. We also explore whether these judgements are affected by personality. Participants recruited from Mechanical Turk rated an emotional support message for Suitability, provided qualitative feedback about their rating and then completed a personality measure. We found that the support message was rated worst when it came from the Computer, Distant-sister and Close-friend. While these were rated worse, they were not rated poorly, implying that support from a computer is valuable. There were three effects for personality which did not vary with the support giver’s Identity: agreeableness and emotional stability had a positive correlation with 3 sub-scales of supportiveness. A thematic analysis of comments revealed that people prefer emotional support from a human; they like empathy; support from close friends means more; they prefer personalised support; and they have higher expectations from family over friends.

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          Most cited references 23

          • Record: found
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          Personality and susceptibility to positive and negative emotional states.

          Gray's (1981) theory suggests that extraverts and neurotics are differentially sensitive to stimuli that generate positive and negative affect, respectively. From this theory it was hypothesized that efficacy of a standard positive-affect induction would be more strongly related to extraversion than to neuroticism scores, whereas efficacy of a standard negative-affect induction would be more strongly related to neuroticism scores. Positive and negative affect was manipulated in a controlled setting, and the effectiveness of the mood induction was assessed using standard mood adjective rating scales. Results are consistent with the hypothesis that neurotic Ss (compared with stable Ss) show heightened emotional reactivity to the negative-mood induction, whereas extraverts (compared with intraverts) show heightened emotional reactivity to the positive-mood induction. Results corroborate and extend previous findings.
            • Record: found
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            • Article: not found

            Social network size in humans.

             R. Hill,  R. Dunbar (2003)
            This paper examines social network size in contemporary Western society based on the exchange of Christmas cards. Maximum network size averaged 153.5 individuals, with a mean network size of 124.9 for those individuals explicitly contacted; these values are remarkably close to the group size of 150 predicted for humans on the basis of the size of their neocortex. Age, household type, and the relationship to the individual influence network structure, although the proportion of kin remained relatively constant at around 21%. Frequency of contact between network members was primarily determined by two classes of variable: passive factors (distance, work colleague, overseas) and active factors (emotional closeness, genetic relatedness). Controlling for the influence of passive factors on contact rates allowed the hierarchical structure of human social groups to be delimited. These findings suggest that there may be cognitive constraints on network size.
              • Record: found
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              • Article: not found

              Higher-order factors of the Big Five in a multi-informant sample.

               Colin DeYoung (2006)
              In a large community sample (N=490), the Big Five were not orthogonal when modeled as latent variables representing the shared variance of reports from 4 different informants. Additionally, the standard higher-order factor structure was present in latent space: Neuroticism (reversed), Agreeableness, and Conscientiousness formed one factor, labeled Stability, and Extraversion and Openness/Intellect formed a second factor, labeled Plasticity. Comparison of two instruments, the Big Five Inventory and the Mini-Markers, supported the hypotheses that single-adjective rating instruments are likely to yield lower interrater agreement than phrase rating instruments and that lower interrater agreement is associated with weaker correlations among the Big Five and a less coherent higher-order factor structure. In conclusion, an interpretation of the higher-order factors is discussed, including possible neurobiological substrates. (c) 2006 APA, all rights reserved.

                Author and article information

                July 2018
                July 2018
                : 1-10
                University of Southampton Southampton, UK
                University of Aberdeen Aberdeen, UK
                © Smith et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                Proceedings of the 32nd International BCS Human Computer Interaction Conference
                Belfast, UK
                4 - 6 July 2018
                Electronic Workshops in Computing (eWiC)
                Human Computer Interaction Conference
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page): https://ewic.bcs.org/
                Electronic Workshops in Computing


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