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Switch to: References
Citations of:
Influencing robot influence : Personalization of persuasive robots
Interaction Studies 22 (3):464-487 (2021)
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Mental or computer simulation of cause and effect of certain behaviors is a recognized approach to changing one’s attitude or triggering an action. Meanwhile, psychology research results suggest that frequency of simulation may affect the corresponding persuasiveness. This paper argues that with always-on sensing and data-driven visualization technologies, interactive tangible systems can be designed to simulate hypothetical outcomes of real-life behaviors in everyday contexts, which repeatedly stimulate users’ imagination of behavioral consequences and thereby behavioral intentions. To investigate the effect, a (...) |
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Previous experimental findings support the hypothesis that laughter and positive emotions are contagious in face-to-face and mediated communication. To test this hypothesis, we describe four experiments in which participants communicate via a chat tool that artificially adds or removes laughter, without participants being aware of the manipulation. We found no evidence to support the contagion hypothesis. However, artificially exposing participants to more lols decreased participants’ use of hahas but led to more involvement and improved task-performance. Similarly, artificially exposing participants to (...) |
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Persuasive social robots can influence human behavior through giving advice. The current study investigates whether references to prior discourse and signals of empathy make an advice-giving robot an even more effective persuader and whether participants follow the robot’s advice and drink even more water when the robot additionally uses these strategies. We recruited students and university staff for a lab-study in which three different robot personalities on the same robot type presented health-related information. In one condition, the robot gave advice (...) |
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Persuasive social robots can influence human behavior through giving advice. The current study investigates whether references to prior discourse and signals of empathy make an advice-giving robot an even more effective persuader and whether participants follow the robot’s advice and drink even more water when the robot additionally uses these strategies. We recruited students and university staff for a lab-study in which three different robot personalities on the same robot type presented health-related information. In one condition, the robot gave advice (...) |
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This special issue addresses how aspects of the communicative situation influence how influential persuasive utterances (or other strategies of influence) are in their contexts of use. Specifically, we study the effects of interactional, speaker-, addressee- and channel-related factors and of the interpersonal relationship between speaker and hearer, as well as the effects of referring to the shared context itself. The papers combined in this special issue provide evidence for the considerable impact of the here and now of the interactional context (...) |
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This special issue addresses how aspects of the communicative situation influence how influential persuasive utterances (or other strategies of influence) are in their contexts of use. Specifically, we study the effects of interactional, speaker-, addressee- and channel-related factors and of the interpersonal relationship between speaker and hearer, as well as the effects of referring to the shared context itself. The papers combined in this special issue provide evidence for the considerable impact of the here and now of the interactional context (...) |
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In this paper, we analyze what effects indicators of a shared situation have on a speaker’s persuasiveness by investigating how a robot’s advice is received when it indicates that it is sharing the situational context with its user. In our experiment, 80 participants interacted with a robot that referred to aspects of the shared context: Face tracking indicated that the robot saw the participant, incremental feedback suggested that the robot was following their actions, and comments about, and gestures towards, the (...) |
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In this paper, we analyze what effects indicators of a shared situation have on a speaker’s persuasiveness by investigating how a robot’s advice is received when it indicates that it is sharing the situational context with its user. In our experiment, 80 participants interacted with a robot that referred to aspects of the shared context: Face tracking indicated that the robot saw the participant, incremental feedback suggested that the robot was following their actions, and comments about, and gestures towards, the (...) |
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