Understanding Implicit User Feedback from Multisensorial and Physiological Data: A case study

Franci Suni-Lopez; Nelly Condori-Fernandez; Alejandro Catala

doi:10.1145/3387940.3391466

Understanding Implicit User Feedback from Multisensorial and Physiological Data: A case study

Franci Suni-Lopez, Nelly Condori-Fernandez, Alejandro Catala

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

Ensuring the quality of user experience is very important for increasing the acceptance likelihood of software applications, which can be affected by several contextual factors that continuously change over time (e.g., emotional state of end-user). Due to these changes in the context, software continually needs to adapt for delivering software services that can satisfy user needs. However, to achieve this adaptation, it is important to gather and understand the user feedback. In this paper, we mainly investigate whether physiological data can be considered and used as a form of implicit user feedback. To this end, we conducted a case study involving a tourist traveling abroad, who used a wearable device for monitoring his physiological data, and a smartphone with a mobile app for reminding him to take his medication on time during four days. Through the case study, we were able to identify some factors and activities as emotional triggers, which were used for understanding the user context. Our results highlight the importance of having a context analyzer, which can help the system to determine whether the detected stress could be considered as actionable and consequently as implicit user feedback.

Original language	English
Title of host publication	ICSEW '20
Subtitle of host publication	Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops
Publisher	Association for Computing Machinery, Inc
Pages	563-569
Number of pages	7
ISBN (Electronic)	9781450379632
DOIs	https://doi.org/10.1145/3387940.3391466
Publication status	Published - 1 Jun 2020
Event	42nd IEEE/ACM International Conference on Software Engineering Workshops, ICSEW 2020 - Seoul, Korea, Republic of Duration: 27 Jun 2020 → 19 Jul 2020

Conference

Conference	42nd IEEE/ACM International Conference on Software Engineering Workshops, ICSEW 2020
Country/Territory	Korea, Republic of
City	Seoul
Period	27/06/20 → 19/07/20

Bibliographical note

Funding Information:
Special thanks go to the volunteer subject in the case study. This work has been supported by the projects: KUSISQA (014-2019-FONDECYT-BM-INC.INV) from the National Fund for Scientific and Technological Development (FONDECYT-PERU) and World Bank, and Datos 4.0 (TIN2016-78011-C4-1-R) supported by MINECO-AEI/FEDER-UE. Alejandro Catala is a Juan de la Cierva Researcher (IJC2018-037522-I). This research is partly funded by the Spanish Ministry of Science, Innovation and Universities (grant RTI2018-099646-B-I00) and the Galician Ministry of Education, University and Professional Training (grant ED431G2019/04). Some of the previous grants were co-funded by the European Regional Development Fund (ERDF/FEDER program).

Publisher Copyright:
© 2020 ACM.

Keywords

Actionable emotion
Case study
Context information
Implicit user feedback
Physiological data

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10.1145/3387940.3391466

Understanding Implicit User Feedback from Multisensorial and Physiological Data A case studyFinal published version, 314 KBLicence: Article 25fa Dutch Copyright Act

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title = "Understanding Implicit User Feedback from Multisensorial and Physiological Data: A case study",

abstract = "Ensuring the quality of user experience is very important for increasing the acceptance likelihood of software applications, which can be affected by several contextual factors that continuously change over time (e.g., emotional state of end-user). Due to these changes in the context, software continually needs to adapt for delivering software services that can satisfy user needs. However, to achieve this adaptation, it is important to gather and understand the user feedback. In this paper, we mainly investigate whether physiological data can be considered and used as a form of implicit user feedback. To this end, we conducted a case study involving a tourist traveling abroad, who used a wearable device for monitoring his physiological data, and a smartphone with a mobile app for reminding him to take his medication on time during four days. Through the case study, we were able to identify some factors and activities as emotional triggers, which were used for understanding the user context. Our results highlight the importance of having a context analyzer, which can help the system to determine whether the detected stress could be considered as actionable and consequently as implicit user feedback. ",

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Suni-Lopez, F, Condori-Fernandez, N & Catala, A 2020, Understanding Implicit User Feedback from Multisensorial and Physiological Data: A case study. in ICSEW '20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops. Association for Computing Machinery, Inc, pp. 563-569, 42nd IEEE/ACM International Conference on Software Engineering Workshops, ICSEW 2020, Seoul, Korea, Republic of, 27/06/20. https://doi.org/10.1145/3387940.3391466

Understanding Implicit User Feedback from Multisensorial and Physiological Data: A case study. / Suni-Lopez, Franci; Condori-Fernandez, Nelly; Catala, Alejandro.
ICSEW '20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops. Association for Computing Machinery, Inc, 2020. p. 563-569.

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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N2 - Ensuring the quality of user experience is very important for increasing the acceptance likelihood of software applications, which can be affected by several contextual factors that continuously change over time (e.g., emotional state of end-user). Due to these changes in the context, software continually needs to adapt for delivering software services that can satisfy user needs. However, to achieve this adaptation, it is important to gather and understand the user feedback. In this paper, we mainly investigate whether physiological data can be considered and used as a form of implicit user feedback. To this end, we conducted a case study involving a tourist traveling abroad, who used a wearable device for monitoring his physiological data, and a smartphone with a mobile app for reminding him to take his medication on time during four days. Through the case study, we were able to identify some factors and activities as emotional triggers, which were used for understanding the user context. Our results highlight the importance of having a context analyzer, which can help the system to determine whether the detected stress could be considered as actionable and consequently as implicit user feedback.

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Understanding Implicit User Feedback from Multisensorial and Physiological Data: A case study

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Keywords

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