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Complementing Embodied Conversational Agents by Implementing Compliments Measuring the Effect of Compliments in Embodied Conversational Agents Group 23.

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Presentation on theme: "Complementing Embodied Conversational Agents by Implementing Compliments Measuring the Effect of Compliments in Embodied Conversational Agents Group 23."— Presentation transcript:

1 Complementing Embodied Conversational Agents by Implementing Compliments Measuring the Effect of Compliments in Embodied Conversational Agents Group 23 Marieke Agterbos | Tim van Bremen | Carel Jansen | Lisa Oud | Justin Post

2 Research Question To what extent do compliments have an impact on the user experience of embodied conversational agents?

3 Questions 1.Are the ECA’s compliments recognized as compliments? (Part I) 2.Experience with vs. without compliments (Part II) A.Perceived liking of the agent B.Perceived level of comfort C.Perceived information quality

4 Background theory  Making machines more human (Picard, 2000)  Minimize gap between real life contact and digital contact  Lifelike ECA (Louwerse et al., 2009)  Is sensitive to moods and sentiments  Politeness and variation in language (Behnam & A. Niloufar, 2011)  Add value and believability  Function of Compliments (Manes en Wolfson, 1981)  Goodwill and solidarity  Three types of personal compliments (Jucker, 2009)  Implicit, explicit or indirect  Behavioral realism might be more important than photorealism (Groom, 2009)  Generating positive response  More productive conversation

5 Pre-test  Are the ECA’s compliments recognized as compliments?  Participants read a transcript of an ECA conversation  Questionnaire on different parts of the conversation: 1. Bot: ‘Hello, how are you?’ 2. User: ‘Great, and you?’ 3. Bot: ‘Good, so am I.’ 4. User: ‘Good.’ 5. Bot: ‘What was the name of the lead guitar player of the band called “A band of Gypsies?”’ 6. User: ‘Jimi Hendrix.’ 7. Bot: ‘That is correct.’ 8. Bot: ‘Someone told me you are very bright.’

6 Pre-test results ‘Yes, this is a significant difference (p<0.01)’  84 participants (53, 31)

7 Pre-test results

8 Experiment Design  Measured variables  Liking  Comfort  Information Quality

9 Experiment  53 Participants  Conversation with bot  Quiz setting  Questionnaire  Perceived liking  Perceived level of comfort  Information quality “How many strings does a guitar have?” “Who is the prime minister of the Netherlands?”

10 Results

11 Effects

12 Results  H1. Contextual compliments have a positive effect on the user experience of an ECA.  H1-a. perceived liking of the agent.  H1-b. perceived level of comfort.  H1-c. perceived quality of information.  H2. Non-Contextual compliments have a positive effect on the user experience of an ECA.  H2-a. perceived liking of the agent.  H2-b. perceived level of comfort.  H2-c. perceived quality of information.  H3. Contextual compliments have a more positive effect than non-contextual compliments.  H3-a. perceived liking of the agent.  H3-b. perceived quality of information.  H3-c. perceived level of comfort.

13 Results  H1. Contextual compliments have a positive effect on non-contextual compliments on the user experience of an ECA.  H2. Non-Contextual compliments have a positive effect on the user experience of an ECA.  H3. Contextual compliments have a more positive effect than non- contextual compliments.  H4. Compliments have a positive effect on the user experience of an ECA.  H4-a. perceived liking of the agent.  H4-b. perceived quality of information.  H4-c. perceived level of comfort.

14 Conclusion  Compliments have a positive effect on the user experience of an ECA.  However, not on likingness.  The type of compliment matters  Non-contextual > contextual

15 Discussion Pros:  Pretest, kind of compliments accounted for.  Pretest in line with experiment outcome.  All experiments under supervision of a test leader. Improvements:  Sample too small  Language, not native language of all subjects  Variable mount of compliments given  Compliments when correctly answered  Definition of comfort, persuasiveness, likeliness might differ individually

16 Questions?

17 Measuring - Liking  ‘I would like to be friends with her’  ‘If I was upset, she would be able to cheer me up.’  ‘She is a bad listener’  Rated on Likert scale 1-7

18 Measuring - Level of comfort  During the conversation, I felt:  Comfortable  Involved  Open  Relaxed  Warm  Rated on Likert scale 1-7

19 Measuring - Information quality  The extent to which the information was:  Correct  Helpful  Persuasive  Insightful  Relevant  Rated on Likert scale 1-7

20 Context  Controlled environment  Participants from same population


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