Detecting Perception of Smartphone Notifications Using Skin Conductance Responses

Fortin, Pascal E.; Sulmont, Elisabeth; Cooperstock, Jeremy R.

doi:10.1145/3290605.3300420

Cited by 16 publications

(3 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, since these rewards may not be immediate in the context of IM, they may create a state of increased emotional arousal, especially when the rewards (i.e., the response) eventually arrive in the form of notifications on the smartphone. Prior research has already shown that arousal induced by smartphone notifications is different from arousal due to arbitrary stimuli in the environment ( Fortin et al, 2019 ). As individuals are notified about incoming messages, “the dopaminergic reward circuit [gets activated], leading the user to anticipate and seek these [social] rewarding notifications” ( Veissière and Stendel, 2018 , p. 4).…”

Section: Discussionmentioning

confidence: 99%

Exploring the Emotional Experience During Instant Messaging Among Young Adults: An Experimental Study Incorporating Physiological Correlates of Arousal

et al. 2022

View full text Add to dashboard Cite

Instant messaging (IM) is a highly diffused form of communication among younger populations, yet little is known about the emotional experience during IM. The present study aimed to investigate the emotional experience during IM by drawing on the Circumplex Model of Affect and measuring heart rate and electrodermal activity as indicators of arousal in addition to self-reported perceived emotional valence. Using an experimental design, we manipulated message latency (i.e., response after 1 min versus 7 min) and message valence (positive versus negative response). Based on data collected from 65 young adults (50% male; Mage = 23.28, SD = 3.75), we observed arousal as participants’ electrodermal activity levels increased from the time a fictitious peer started typing a response to the receipt of that response, especially in the delayed condition. Electrodermal activity levels also increased in both the positive and the negative message conditions. No changes were observed for heart rate. Participants’ self-report perceived emotional valence revealed that positive messages were evaluated as more pleasant and the peer as more available, while no difference in the self-report was found for message latency. These findings shed light on the emotional experience during IM by adding valuable insights on the physiological processes underlying the anticipation of social reward, but only during delayed IM exchange that can be observed in Human–Computer-Interaction.

show abstract

Section: Discussionmentioning

confidence: 99%

Exploring the Emotional Experience During Instant Messaging Among Young Adults: An Experimental Study Incorporating Physiological Correlates of Arousal

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Name • Logistic Regression: As a popular statistical tool in HCI and CSCW quantitative analysis [21,38,56,69], Logistic Regression in its basic form uses a logistic (sigmoid function) function to model a binary dependent variable [69]. In our work, the dependent variable is the dropout's outcome [69].…”

Section: Models With Hmm Engagement Features (Ef) Models Without Hmm ...mentioning

confidence: 99%

Characterizing Student Engagement Moods for Dropout Prediction in Question Pool Websites

Mogavi,

Ma,

Hui

2021

Preprint

View full text Add to dashboard Cite

Problem-Based Learning (PBL) is a popular approach to instruction that supports students to get hands-on training by solving problems. Question Pool websites (QPs) such as LeetCode, Code Chef, and Math Playground help PBL by supplying authentic, diverse, and contextualized questions to students. Nonetheless, empirical findings suggest that 40% to 80% of students registered in QPs drop out in less than two months. This research is the first attempt to understand and predict student dropouts from QPs via exploiting students' engagement moods. Adopting a data-driven approach, we identify five different engagement moods for QP students, which are namely challenge-seeker, subject-seeker, interest-seeker, joy-seeker, and non-seeker. We find that students have collective preferences for answering questions in each engagement mood, and deviation from those preferences increases their probability of dropping out significantly. Last but not least, this paper contributes by introducing a new hybrid machine learning model (we call Dropout-Plus) for predicting student dropouts in QPs. The test results on a popular QP in China, with nearly 10K students, show that Dropout-Plus can exceed the rival algorithms' dropout prediction performance in terms of accuracy, F1-measure, and AUC. We wrap up our work by giving some design suggestions to QP managers and online learning professionals to reduce their student dropouts.CCS Concepts: • Human-centered computing → HCI theory, concepts and models; • Applied computing → Interactive learning environments; • Computing methodologies → Machine learning approaches.

show abstract

“…Although several studies have examined the negative impact of smartphone addiction [47][48][49][50][51][52][53][54], little is known regarding its behavioral and physiological basis, especially in the context of mother-infant interactions. A major way in which we can assess reactivity to smartphone distraction during mother-infant interaction is by measuring changes in physiological function of mothers' peripheral nervous system as well as her gaze patterns during interactions with her infant that also involve the smartphone.…”

Section: Introductionmentioning

confidence: 99%

The relationship between maternal smartphone use, physiological responses, and gaze patterns during breastfeeding and face-to-face interactions with infant

Nomkin

Gordon

2021

PLoS ONE

View full text Add to dashboard Cite

Smartphone use during parent-child interactions is highly prevalent, however, there is a lack of scientific knowledge on how smartphone use during breastfeeding or face-to-face interactions may modulate mothers’ attentive responsiveness towards the infant as well as maternal physiological arousal. In the present study, we provide the first evidence for the influence of the smartphone on maternal physiological responses and her attention towards the infant during breastfeeding and face-to-face interactions. Twenty breastfeeding mothers and their infants participated in this lab study during which electrodermal activity, cardiograph impedance, and gaze patterns were monitored in breastfeeding and face-to-face interactions with three conditions manipulating the level of maternal smartphone involvement. We report that mothers’ gaze toward their infants decreased when breastfeeding while using the smartphone compared to face-to-face interaction. Further, we show that greater maternal electrodermal activity and cardiac output were related to longer maternal gaze fixation toward the smartphone during breastfeeding. Finally, results indicate that mothers’ smartphone addiction levels were negatively correlated with electrodermal activity during breastfeeding. This study provides an initial basis for much required further research that will explore the influence of smartphone use on maternal biobehavioral responses in this digital age and the consequences for infant cognitive, emotional, and social development.

show abstract

Detecting Perception of Smartphone Notifications Using Skin Conductance Responses

Cited by 16 publications

References 16 publications

Exploring the Emotional Experience During Instant Messaging Among Young Adults: An Experimental Study Incorporating Physiological Correlates of Arousal

Exploring the Emotional Experience During Instant Messaging Among Young Adults: An Experimental Study Incorporating Physiological Correlates of Arousal

Characterizing Student Engagement Moods for Dropout Prediction in Question Pool Websites

The relationship between maternal smartphone use, physiological responses, and gaze patterns during breastfeeding and face-to-face interactions with infant

Contact Info

Product

Resources

About