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Mimicry and expressiveness of an ECA in human-agent interaction: familiarity breeds content!

Overview of attention for article published in Computational Cognitive Science, June 2016
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Title
Mimicry and expressiveness of an ECA in human-agent interaction: familiarity breeds content!
Published in
Computational Cognitive Science, June 2016
DOI 10.1186/s40469-016-0008-2
Pubmed ID
Authors

Catherine J. Stevens, Bronwyn Pinchbeck, Trent Lewis, Martin Luerssen, Darius Pfitzner, David M. W. Powers, Arman Abrahamyan, Yvonne Leung, Guillaume Gibert

Abstract

Two experiments investigated the effect of features of human behaviour on the quality of interaction with an Embodied Conversational Agent (ECA). In Experiment 1, visual prominence cues (head nod, eyebrow raise) of the ECA were manipulated to explore the hypothesis that likeability of an ECA increases as a function of interpersonal mimicry. In the context of an error detection task, the ECA either mimicked or did not mimic a head nod or brow raise that humans produced to give emphasis to a word when correcting the ECA's vocabulary. In Experiment 2, presence versus absence of facial expressions on comprehension accuracy of two computer-driven ECA monologues was investigated. In Experiment 1, evidence for a positive relationship between ECA mimicry and lifelikeness was obtained. However, a mimicking agent did not elicit more human gestures. In Experiment 2, expressiveness was associated with greater comprehension and higher ratings of humour and engagement. Influences from mimicry can be explained by visual and motor simulation, and bidirectional links between similarity and liking. Cue redundancy and minimizing cognitive load are potential explanations for expressiveness aiding comprehension.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 27%
Student > Master 9 22%
Researcher 6 15%
Student > Bachelor 4 10%
Professor > Associate Professor 4 10%
Other 5 12%
Unknown 2 5%
Readers by discipline Count As %
Computer Science 14 34%
Psychology 9 22%
Engineering 5 12%
Linguistics 1 2%
Economics, Econometrics and Finance 1 2%
Other 4 10%
Unknown 7 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 December 2020.
All research outputs
#15,875,372
of 19,763,264 outputs
Outputs from Computational Cognitive Science
#4
of 5 outputs
Outputs of similar age
#280,394
of 384,844 outputs
Outputs of similar age from Computational Cognitive Science
#1
of 1 outputs
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