research-article

A study of mobile mood awareness and communication through MobiMood

Authors:

Nuria OliverAuthors Info & Claims

NordiCHI '10: Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries

Pages 128 - 137

https://doi.org/10.1145/1868914.1868933

Published: 16 October 2010 Publication History

Abstract

Recent research shows that there has been increased interest in investigating the role of mood and emotions in the HCI domain. Our moods, however, are complex. They are affected by many dynamic factors and can change multiple times throughout each day. Furthermore, our mood can have significant implications in terms of our experiences, our actions and most importantly on our interactions with other people. We have developed MobiMood, a proof-of-concept social mobile application that enables groups of friends to share their moods with each other. In this paper, we present the results of an exploratory field study of MobiMood, focusing on explicit mood sharing in-situ. Our results highlight that certain contextual factors had an effect on mood and the interpretation of moods. Furthermore, mood sharing and mood awareness appear to be good springboards for conversations and increased communication among users. These and other findings lead to a number of key implications in the design of mobile social awareness applications.

References

[1]

L. Barkhuus, B. Brown, M. Bell, S. Sherwood, M. Hall, and M. Chalmers. From awareness to repartee: sharing location within social groups. In Proceedings of CHI'08, pages 497--506. ACM, 2008.

Digital Library

[2]

N. Belloni, L. E. Holmquist, and J. Tholander. See you on the subway: exploring mobile social software. In Proceedings of CHI'09 Extended Abstracts, pages 4543--4548. ACM, 2009.

Digital Library

[3]

F. Bentley and C. J. Metcalf. The use of mobile social presence. IEEE Pervasive Computing, 8(4):35--41, 2009.

Digital Library

[4]

K. Boehner, M. Chen, and Z. Liu. Reflector: An emergent impression of collective experience. In Proceedings of the CHI Workshop on Providing Elegant Peripheral Awareness. ACM Press, 2003.

[5]

J. Bollen and A. P. H. Mao. Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena. In Proceedings of WWW '10, pages 1--3. ACM, 2009. to appear.

[6]

C. Crumlish and E. Malone. Designing Social Interfaces: Principles, Patterns, and Practices for Improving the User Experience. O'Reilly, 2009.

[7]

A. Geven, M. Tscheligi, and L. Noldus. Measuring mobile emotions: Measuring the impossible? In Proceedings of MobileHCI'09, pages 1--3. ACM, 2009.

Digital Library

[8]

A. J. Gill, D. Gergle, R. M. French, and J. Oberlander. Emotion rating from short blog texts. In CHI '08: Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems, pages 1121--1124. ACM, 2008.

Digital Library

[9]

A. Gluhak, M. Presser, L. Zhu, and S. Esfandiyari. Towards mood based mobile services and applications. In Smart Sensing and Context, 4793/2007:159--174, 2007.

Digital Library

[10]

W. Griswold, P. Shanahan, S. Brown, and R. Boyer. Activecampus: Experiments in community-oriented ubiquitous computing. IEEE Computer, 37(10), 2003.

Digital Library

[11]

J. Koolwaaij, A. Tarlano, M. Luther, and P. Nurmi. Context watcher - sharing context information in everyday life. In Proceedings of Web Technologies, Applications and Services, 2006.

[12]

G. Lane, S. Thelwall, A. Angus, V. Peckett, N., and West. Urban tapestries: Public authoring, place and mobility, 2005. Project final report, Proboscis, UK, London, UK, 2005.

[13]

G. Leshed and J. J. Kaye. Understanding how bloggers feel: recognizing affect in blog posts. In CHI '06: CHI '06 extended abstracts on Human factors in computing systems, pages 1019--1024. ACM, 2006.

Digital Library

[14]

M. Luther, S. Bohm, M. Wagner, and J. Koolwaaij. Enhanced presence tracking for mobile applications. In ISWC '05: Proceedings of the International Semantic Web Conference, 2005.

[15]

N. Marmasse, C. Schmandt, and D. Spectre. Watchme: Communication and awareness between members of a closely-knit group. In Ubicomp, volume 3205 of Lecture Notes in Computer Science, pages 214--231. Springer, 2004.

[16]

C. McIntyre, L. Clark, and S. Cross. The effect of induced social interaction on positive and negatives affect. Bulletin of the Psychonomic Society, 29:67--70, 1991.

[17]

M. Morris. Technologies for heart and mind: New directions in embedded assessment. Intel Technology Journal, 11(1), 2007.

[18]

P. Persson and P. Fagerberg. Geonotes: a real-use study of a public location-aware community system, 2002. Technical Report SICS-T-2002/27-SE, SICS, University of Göteborg, Sweden, 2002.

[19]

J. Russell. Aa circumplex model of affect. Journal of Personality and Social Psychology, 39:1161, 1980.

[20]

P. Saint-Andre. Extensible messaging and presence protocol (xmpp): Instant messaging and presence, 2004. IETF RFC 3291.

[21]

A. S. Shirazi, F. Alt, A. Schmidt, A.-H. Sarjanoja, L. Hynninen, J. Häkkilä, and P. Holleis. Emotion sharing via self-composed melodies on mobile phones. In Proceedings of MobileHCI'08, pages 1--4. ACM, 2009.

Digital Library

[22]

I. Smith, S. Consolvo, A. Lamarca, J. Hightower, J. Scott, T. Sohn, J. Hughes, G. Iachello, and G. D. Abowd. Social disclosure of place: From location technology to communication practices. IEEE Pervasive Computing, 3468:134--151, 2005.

Digital Library

[23]

P. Sundström, A. Ståhl, and K. Höök. In situ informants exploring an emotional mobile messaging system in their everyday practice. International Journal of Human-Computer Studies, 65(4):388--403, 2007.

Digital Library

[24]

J. R. Vittengl and C. S. Holt. A time-series diary study of mood and social interaction. Motivation and Emotion, 22(3):255--275, 1998.

[25]

H. Wang, H. Prendinger, and T. Igarashi. Communicating emotions in online chat using physiological sensors and animated text. In Proceedings of CHI '04 extended abstracts, pages 1171--1174. ACM, 2004.

Digital Library

[26]

L. Wexner. The degree to which color (hues) are associated with mood-tones. The Journal of Applied Psychology, 38(6):432--435, 1954.

Cited By

Priyam Jyoti Das Pdiangmon Kyndait Sungjemrenla I Jamir Dhiraj Baishya Juganta Kumar Kalita Lobsang Tenzing Komu (2024)The Role of Technology in Mental Health: Evaluating Digital Interventions for Psychological Well-beingInternational Journal of Scientific Research in Science and Technology10.32628/IJSRST2411618611:6(366-386)Online publication date: 30-Nov-2024
https://doi.org/10.32628/IJSRST24116186
Shania MHandayani PAsih S(2023)Designing High-Fidelity Mobile Health for Depression in Indonesian Adolescents Using Design Science Research: Mixed Method ApproachesJMIR Formative Research10.2196/489137(e48913)Online publication date: 3-Jul-2023
https://doi.org/10.2196/48913
Nafees MSaxena NCardenas AGrijalva SBurnap P(2023)Smart Grid Cyber-Physical Situational Awareness of Complex Operational Technology Attacks: A ReviewACM Computing Surveys10.1145/356557055:10(1-36)Online publication date: 2-Feb-2023
https://dl.acm.org/doi/10.1145/3565570
Show More Cited By

Index Terms

A study of mobile mood awareness and communication through MobiMood
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods

Recommendations

Interactions with a moody robot
HRI '06: Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction

This paper reports on the results of a long-term experiment in which a social robot's facial expressions were changed to reflect different moods. While the facial changes in each condition were not extremely different, they still altered how people ...
Emojis influence emotional communication, social attributions, and information processing
Abstract
Many emojis symbolize nonverbal cues that are used during face-to-face communication. Despite their popularity, few studies have examined how emojis influence digital interactions. The present study addresses this gap by measuring the ...
Highlights
- Emojis convey information about the sender's affect.
- Senders that use positive ...
Programmer's mood and their performance
ECCE '06: Proceedings of the 13th Eurpoean conference on Cognitive ergonomics: trust and control in complex socio-technical systems

Moods might influence the quality and performance of programmers while programming. It is evident from literature that positive and negative moods influence divergent thinking, quantity/quality of ideas and creative problem solving (Vosburg, 1998). The ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

NordiCHI '10: Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries

October 2010

889 pages

ISBN:9781605589343

DOI:10.1145/1868914

General Chairs:
Ebba Þóra Hvannberg
University of Iceland, Iceland
,
Marta Kristín Lárusdóttir
Reykjavik University, Iceland
,
Program Chairs:
Ann Blandford
University College London
,
Jan Gulliksen
Royal Institute of Technology, Sweden

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Reykjavik University
University of Iceland

In-Cooperation

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 October 2010

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

NordiCHI '10

Sponsor:

NordiCHI '10: 6th Nordic Conference on Human-Computer Interaction

October 16 - 20, 2010

Reykjavik, Iceland

Acceptance Rates

Overall Acceptance Rate 379 of 1,572 submissions, 24%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

53
Total Citations
View Citations
692
Total Downloads

Downloads (Last 12 months)38
Downloads (Last 6 weeks)2

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Priyam Jyoti Das Pdiangmon Kyndait Sungjemrenla I Jamir Dhiraj Baishya Juganta Kumar Kalita Lobsang Tenzing Komu (2024)The Role of Technology in Mental Health: Evaluating Digital Interventions for Psychological Well-beingInternational Journal of Scientific Research in Science and Technology10.32628/IJSRST2411618611:6(366-386)Online publication date: 30-Nov-2024
https://doi.org/10.32628/IJSRST24116186
Shania MHandayani PAsih S(2023)Designing High-Fidelity Mobile Health for Depression in Indonesian Adolescents Using Design Science Research: Mixed Method ApproachesJMIR Formative Research10.2196/489137(e48913)Online publication date: 3-Jul-2023
https://doi.org/10.2196/48913
Nafees MSaxena NCardenas AGrijalva SBurnap P(2023)Smart Grid Cyber-Physical Situational Awareness of Complex Operational Technology Attacks: A ReviewACM Computing Surveys10.1145/356557055:10(1-36)Online publication date: 2-Feb-2023
https://dl.acm.org/doi/10.1145/3565570
Kruzan KNg AStiles-Shields CLattie EMohr DReddy M(2023)The Perceived Utility of Smartphone and Wearable Sensor Data in Digital Self-tracking Technologies for Mental HealthProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581209(1-16)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581209
Sarsenbayeva ZFleming CTag BWithana Avan Berkel NMcEwan A(2023)A Review on Mood Assessment Using SmartphonesHuman-Computer Interaction – INTERACT 202310.1007/978-3-031-42283-6_22(385-413)Online publication date: 25-Aug-2023
https://doi.org/10.1007/978-3-031-42283-6_22
Wang DMuller MYang QWang ZTan MHobson S(2022)Organizational Distance Also MattersProceedings of the ACM on Human-Computer Interaction10.1145/35555546:CSCW2(1-18)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555554
Hadi Mogavi RHaq EGujar SHui PMa X(2022)More Gamification Is Not Always BetterProceedings of the ACM on Human-Computer Interaction10.1145/35555536:CSCW2(1-32)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555553
Yang MLee KKim ESong YLee SKang JHan JSong HKim T(2022)Magic Brush: An AI-based Service for Dementia Prevention focused on Intrinsic MotivationProceedings of the ACM on Human-Computer Interaction10.1145/35555496:CSCW2(1-21)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555549
Hoffmann SPinatti de Carvalho ASchweitzer MAbele NWulf V(2022)Producing and Consuming Instructional Material in Manufacturing Contexts: Evaluation of an AR-based Cyber-Physical Production System for Supporting Knowledge and Expertise SharingProceedings of the ACM on Human-Computer Interaction10.1145/35550916:CSCW2(1-36)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555091
Da Silva JJensen R(2022)"Cyber security is a dark art": The CISO as SoothsayerProceedings of the ACM on Human-Computer Interaction10.1145/35550906:CSCW2(1-31)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.1145/3555090
Show More Cited By

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.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten