abstract

I Understand Your Frustration

Authors:

Guy Feigenblat,

David Konopnicki,

Michal Shmueli-Scheuer,

Jonathan Herzig,

Hen ShkediAuthors Info & Claims

CSCW '16 Companion: Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion

Pages 25 - 28

https://doi.org/10.1145/2818052.2874316

Published: 27 February 2016 Publication History

Get Access

Abstract

The use of emotional intelligence in a conversation has a significant positive effect on customer satisfaction and can help resolve difficult conflicts. Many enterprises use virtual agents that automatically interact with customers across a variety of interaction channels. However, these agents have no emotional intelligence and cannot express themselves in an empathic manner. This demo demonstrates the use of emotional intelligence in a technical conversation with a customer. The agent is augmented with emotion sensing capabilities, which allow him to detect expressed emotions, and reply in an appropriate manner by expressing empathy, for example.

References

[1]

Robert Bacal. 2010. Perfect Phrases for Customer Service. McGraw-Hill Education.

Google Scholar

[2]

Paul Ekman. 1992. An argument for basic emotions. Cognition & Emotion 6, 3-4 (1992), 169-200.

Crossref

Google Scholar

[3]

Katja Gelbrich. 2010. Anger, frustration, and helplessness after service failure: coping strategies and effective informational support. Journal of the Academy of Marketing Science 38, 5 (2010), 567-585.

Crossref

Google Scholar

[4]

Narendra K. Gupta, Mazin Gilbert, and Giuseppe Di Fabbrizio. 2013. Emotion Detection in Email Customer Care. Computational Intelligence 29, 3 (2013), 489-505.

Crossref

Google Scholar

[5]

Saif Mohammad. 2012. Portable features for classifying emotional text. In Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics, 587-591.

Digital Library

Google Scholar

[6]

Richard L Oliver. 2014. Satisfaction: A behavioral perspective on the consumer. Routledge.

Crossref

Google Scholar

[7]

Matthew Purver and Stuart Battersby. 2012. Experimenting with distant supervision for emotion classification. In Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, 482-491.

Digital Library

Google Scholar

[8]

Anat Rafaeli and Robert I Sutton. 1987. Expression of emotion as part of the work role. Academy of management review 12, 1 (1987), 23-37.

Google Scholar

[9]

Kirk Roberts, Michael A Roach, Joseph Johnson, Josh Guthrie, and Sanda M Harabagiu. 2012. EmpaTweet: Annotating and Detecting Emotions on Twitter. In LREC. 3806- 3813.

Google Scholar

[10]

Luis-Felipe Rodríguez and Félix Ramos. 2014. Development of computational models of emotions for autonomous agents: a review. Cognitive Computation 6, 3 (2014), 351-375.

Crossref

Google Scholar

Cited By

View all

Ge XLi DGuan DXu SSun YZhou M(2019)Do Smart Speakers Respond to Their Errors Properly? A Study on Human-Computer Dialogue StrategyDesign, User Experience, and Usability. User Experience in Advanced Technological Environments10.1007/978-3-030-23541-3_32(440-455)Online publication date: 3-Jul-2019
https://doi.org/10.1007/978-3-030-23541-3_32
Sandbank TShmueli-Scheuer MHerzig JKonopnicki DShaul RPapadopoulos GKuflik TChen FDuarte CFu W(2017)EHCToolCompanion Proceedings of the 22nd International Conference on Intelligent User Interfaces10.1145/3030024.3038260(125-128)Online publication date: 7-Mar-2017
https://dl.acm.org/doi/10.1145/3030024.3038260
Herzig JFeigenblat GShmueli-Scheuer MKonopnicki DRafaeli AVassileva JBlustein JAroyo LD'Mello S(2016)Predicting Customer Satisfaction in Customer Support Conversations in Social Media Using Affective FeaturesProceedings of the 2016 Conference on User Modeling Adaptation and Personalization10.1145/2930238.2930285(115-119)Online publication date: 13-Jul-2016
https://dl.acm.org/doi/10.1145/2930238.2930285

Recommendations

Enhancing Conversational Agents with Empathic Abilities
IVA '21: Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents

Conversational agents are getting increasingly popular and find applications in health and customer services. Conversations in these fields are often emotionally charged. It is, therefore, necessary to handle the conversation with some degree of empathy ...
The effectiveness of social agents in reducing user frustration
CHI EA '06: CHI '06 Extended Abstracts on Human Factors in Computing Systems

A study was conducted to evaluate the effectiveness of social agents in reducing user frustration. The particular type of agent studied reacted to users' facial expressions while they browsed through a shopping website. While highly frustrated users ...
A formal model of emotions for an empathic rational dialog agent

Recent research has shown that virtual agents expressing empathic emotions toward users have the potential to enhance human---machine interaction. To provide empathic capabilities to a rational dialog agent, we propose a formal model of emotions based ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

CSCW '16 Companion: Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion

February 2016

549 pages

ISBN:9781450339506

DOI:10.1145/2818052

General Chairs:
Darren Gergle
Northwestern University
,
Meredith Ringel Morris
Microsoft Research
,
Program Chairs:
Pernille Bjørn
University of Copenhagen
,
Joseph Konstan
University of Minnesota

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 February 2016

Check for updates

Author Tags

Qualifiers

Abstract

Conference

CSCW '16

Sponsor:

SIGCHI

CSCW '16: Computer Supported Cooperative Work and Social Computing

February 26 - March 2, 2016

California, San Francisco, USA

Acceptance Rates

Overall Acceptance Rate 2,235 of 8,521 submissions, 26%

Upcoming Conference

CSCW '25

Sponsor:
sigchi

Computer-Supported Cooperative Work and Social Computing

October 18 - 22, 2025

Bergen , Norway

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
360
Total Downloads

Downloads (Last 12 months)11
Downloads (Last 6 weeks)2

Reflects downloads up to 30 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Ge XLi DGuan DXu SSun YZhou M(2019)Do Smart Speakers Respond to Their Errors Properly? A Study on Human-Computer Dialogue StrategyDesign, User Experience, and Usability. User Experience in Advanced Technological Environments10.1007/978-3-030-23541-3_32(440-455)Online publication date: 3-Jul-2019
https://doi.org/10.1007/978-3-030-23541-3_32
Sandbank TShmueli-Scheuer MHerzig JKonopnicki DShaul RPapadopoulos GKuflik TChen FDuarte CFu W(2017)EHCToolCompanion Proceedings of the 22nd International Conference on Intelligent User Interfaces10.1145/3030024.3038260(125-128)Online publication date: 7-Mar-2017
https://dl.acm.org/doi/10.1145/3030024.3038260
Herzig JFeigenblat GShmueli-Scheuer MKonopnicki DRafaeli AVassileva JBlustein JAroyo LD'Mello S(2016)Predicting Customer Satisfaction in Customer Support Conversations in Social Media Using Affective FeaturesProceedings of the 2016 Conference on User Modeling Adaptation and Personalization10.1145/2930238.2930285(115-119)Online publication date: 13-Jul-2016
https://dl.acm.org/doi/10.1145/2930238.2930285

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Recommendations

Enhancing Conversational Agents with Empathic Abilities

The effectiveness of social agents in reducing user frustration

A formal model of emotions for an empathic rational dialog agent

Comments

Information

Published In

Sponsors

Publisher

Publication History

Check for updates

Author Tags

Qualifiers

Conference

Acceptance Rates

Upcoming Conference

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations