Web Intelligence and Intelligent Agents 2010
DOI: 10.5772/8384
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Towards Socialized Machines: Emotions and Sense of Humour in Conversational Agents

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Cited by 10 publications
(18 citation statements)
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“…We found 12 studies that report personality issues for chatbots. In some studies, personality was investigated in reference to the Big Five model [Mairesse and Walker 2009;Morris 2002;Sjödén et al 2011], while two studies focused on sense of humor [Meany and Clark 2010;Ptaszynski et al 2010]. Three studies investigated the impact of the personality of tutor chatbots on students' engagement [Ayedoun et al 2017;Kumar et al 2010;Sjödén et al 2011 The surveyed literature revealed two benefits of attributing personality to chatbots:…”
Section: Personalitymentioning
confidence: 99%
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“…We found 12 studies that report personality issues for chatbots. In some studies, personality was investigated in reference to the Big Five model [Mairesse and Walker 2009;Morris 2002;Sjödén et al 2011], while two studies focused on sense of humor [Meany and Clark 2010;Ptaszynski et al 2010]. Three studies investigated the impact of the personality of tutor chatbots on students' engagement [Ayedoun et al 2017;Kumar et al 2010;Sjödén et al 2011 The surveyed literature revealed two benefits of attributing personality to chatbots:…”
Section: Personalitymentioning
confidence: 99%
“…[B1] to exhibit believable behavior: [Morris 2002] states that chatbots should have a personality, defined by the Five Factor model plus characteristics such as temperament and tolerance, in order to build utterances using linguistic choices that coheres with these attributions. When evaluating a joking chatbot, [Ptaszynski et al 2010] compared the naturalness of the chatbot's inputs and the chatbot's human-likeness compared to a no-joking chatbot. The joking chatbot scored significantly higher in both constructs.…”
Section: Personalitymentioning
confidence: 99%
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“…Dybala et al [8] developed talking agents that used humour during dialogues: their system selected a keyword from a user utterance and then outputted a short verbal humour statement. Moreover, Ptaszynski et al [10] furthered their system to integrate an emotion analysis engine. Taking into consideration users' utterances and emotional reactions, the engine was able to detect when it was appropriate to tell a joke or not.…”
Section: Background In Computational Humourmentioning
confidence: 99%