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Notice of retraction
Vol. 34, No. 8(3), S&M3042

Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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Sensors and Materials, Volume 32, Number 2(2) (2020)
Copyright(C) MYU K.K.
pp. 723-733
S&M2132 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2020.2676
Published: February 20, 2020

Social Networking Services Support Application Based on Biological Information [PDF]

Chen Feng, Peeraya Sripian, and Midori Sugaya

(Received October 30, 2019; Accepted January 22, 2020)

Keywords: social networking services, emotion, biological sensors, feedback

These days, Internet services realize computer-mediated social communication as social networking services (SNSs) such as WhatsApp, Facebook, Twitter, and so on, which expand worldwide. Through these SNSs, people express emotions by selecting phrases and characters. These emotional expressions are selected generally on the basis of the user’s subjective idea. However, when users lose self-control, they might send inappropriate expressions to others without proper consideration. To avoid such situations, some observable mechanisms that can detect and communicate unconscious emotions to users before they send the message are desired. Recently, some approaches to detecting unconscious emotions using biological sensors have been reported. These approaches provide procedures to make unconscious emotions observable and communicable to users in real time. We combine a biofeedback method with an unconscious emotion estimation method for detecting mismatch between an unconscious emotion and an outward expression before sending the message. Using this idea, we design and implement a system that detects such mismatch and gives feedback to an SNS user. We carry out an experiment using the proposed system. The results show that the system is helpful for the intended purpose but needs improvement.

Corresponding author: Chen Feng


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This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Chen Feng, Peeraya Sripian, and Midori Sugaya, Social Networking Services Support Application Based on Biological Information, Sens. Mater., Vol. 32, No. 2, 2020, p. 723-733.



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