Citation

Reciprocity in Computer-Human Interaction: Source-Based, Norm-Based, and Affect-Based Explanations

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Abstract:

Individuals often apply social rules when they interact with computers, or known as the Computer are Social Actors effect. Following previous work, one approach to understand the mechanism responsible for CASA is to utilize computer agents and have the agents attempt to gain compliance from human partners. The current study focuses on three key factors frequently cited to influence traditional notions of compliance: normative influence (e.g., reciprocity), evaluations toward the source (e.g., competence and warmth), and affective influence (e.g., mood). Structural equation modeling tested a path model to assess the effects of these factors on human compliance to computer request. The final model suggested that normative influence (e.g., receiving help from a computer agent) increased the likelihood of compliance. On the other hand, evaluations toward the computer agent, specifically perceived competence and warmth, did not significantly influence compliance. The discussion includes implications for practitioners and directions for future research.

Most Common Document Word Stems:

comput (134), agent (109), complianc (99), human (87), interact (75), reciproc (69), effect (57), help (57), particip (53), base (51), affect (47), social (47), individu (47), sourc (44), request (44), computer-human (41), compet (41), perceiv (40), mood (38), warmth (38), user (37),
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Association:
Name: International Communication Association 64th Annual Conference
URL:
http://www.icahdq.org


Citation:
URL: http://citation.allacademic.com/meta/p716238_index.html
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MLA Citation:

Lee, Seungcheol. and Liang, Yuhua. "Reciprocity in Computer-Human Interaction: Source-Based, Norm-Based, and Affect-Based Explanations" Paper presented at the annual meeting of the International Communication Association 64th Annual Conference, Seattle Sheraton Hotel, Seattle, Washington, May 21, 2014 <Not Available>. 2018-09-05 <http://citation.allacademic.com/meta/p716238_index.html>

APA Citation:

Lee, S. A. and Liang, Y. , 2014-05-21 "Reciprocity in Computer-Human Interaction: Source-Based, Norm-Based, and Affect-Based Explanations" Paper presented at the annual meeting of the International Communication Association 64th Annual Conference, Seattle Sheraton Hotel, Seattle, Washington Online <APPLICATION/PDF>. 2018-09-05 from http://citation.allacademic.com/meta/p716238_index.html

Publication Type: Conference Paper/Unpublished Manuscript
Review Method: Peer Reviewed
Abstract: Individuals often apply social rules when they interact with computers, or known as the Computer are Social Actors effect. Following previous work, one approach to understand the mechanism responsible for CASA is to utilize computer agents and have the agents attempt to gain compliance from human partners. The current study focuses on three key factors frequently cited to influence traditional notions of compliance: normative influence (e.g., reciprocity), evaluations toward the source (e.g., competence and warmth), and affective influence (e.g., mood). Structural equation modeling tested a path model to assess the effects of these factors on human compliance to computer request. The final model suggested that normative influence (e.g., receiving help from a computer agent) increased the likelihood of compliance. On the other hand, evaluations toward the computer agent, specifically perceived competence and warmth, did not significantly influence compliance. The discussion includes implications for practitioners and directions for future research.


Similar Titles:
Computer Agents Teaching Helping Interactions Effectively (CATHIE): An Agent-based Training System Designed to Teach Empathetic Communication Skills

Social Snacking With a Virtual Agent: On the Interrelation of Need to Belong and Social Effects of Rapport When Interacting With Artificial Entities

Effects of Individual versus Interactive Task Performance through Voice-based Computer-mediated Communication on L2 Learning

Are Physically Embodied Social Agents Better Than Disembodied Social Agents?: Effects of Embodiment, Tactile Interaction, and People’s Loneliness in Human-Robot Interaction


 
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