research-article

Sad or just jealous? Using Experience Sampling to Understand and Detect Negative Affective Experiences on Instagram

Authors:

Mintra Ruensuk,

Ian OakleyAuthors Info & Claims

CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Article No.: 147, Pages 1 - 18

https://doi.org/10.1145/3491102.3517561

Published: 28 April 2022 Publication History

Abstract

Social Network Services (SNSs) evoke diverse affective experiences. While most are positive, many authors have documented both the negative emotions that can result from browsing SNS and their impact: Facebook depression is a common term for the more severe results. However, while the importance of the emotions experienced on SNSs is clear, methods to catalog them, and systems to detect them, are less well developed. Accordingly, this paper reports on two studies using a novel contextually triggered Experience Sampling Method to log surveys immediately after using Instagram, a popular image-based SNS, thus minimizing recall biases. The first study improves our understanding of the emotions experienced while using SNSs. It suggests that common negative experiences relate to appearance comparison and envy. The second study captures smartphone sensor data during Instagram sessions to detect these two emotions, ultimately achieving peak accuracies of 95.78% (binary appearance comparison) and 93.95% (binary envy).

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Cited By

Gebhardt CBrombach ALuong THilliges OHolz C(2024)Detecting Users' Emotional States during Passive Social Media UseProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36596068:2(1-30)Online publication date: 15-May-2024
https://dl.acm.org/doi/10.1145/3659606
Kim JLee DHan MKim JKostakos VOakley I(2024)Unpacking Instagram use: The impact of upward social comparisons on usage patterns and affective experiences in the wildInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2024.103323190(103323)Online publication date: Oct-2024
https://doi.org/10.1016/j.ijhcs.2024.103323
Orzikulova ACho HChung HHong HLee ULee S(2023)FinerMe: Examining App-level and Feature-level Interventions to Regulate Mobile Social Media UseProceedings of the ACM on Human-Computer Interaction10.1145/36100657:CSCW2(1-30)Online publication date: 4-Oct-2023
https://dl.acm.org/doi/10.1145/3610065

Index Terms

Sad or just jealous? Using Experience Sampling to Understand and Detect Negative Affective Experiences on Instagram
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI
  2. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools
    2. Ubiquitous and mobile devices
      1. Smartphones

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CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

April 2022

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ISBN:9781450391573

DOI:10.1145/3491102

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Toyota Research Institute, USA
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Microsoft Research, USA
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University of Tokyo, Japan

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Cited By

Gebhardt CBrombach ALuong THilliges OHolz C(2024)Detecting Users' Emotional States during Passive Social Media UseProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36596068:2(1-30)Online publication date: 15-May-2024
https://dl.acm.org/doi/10.1145/3659606
Kim JLee DHan MKim JKostakos VOakley I(2024)Unpacking Instagram use: The impact of upward social comparisons on usage patterns and affective experiences in the wildInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2024.103323190(103323)Online publication date: Oct-2024
https://doi.org/10.1016/j.ijhcs.2024.103323
Orzikulova ACho HChung HHong HLee ULee S(2023)FinerMe: Examining App-level and Feature-level Interventions to Regulate Mobile Social Media UseProceedings of the ACM on Human-Computer Interaction10.1145/36100657:CSCW2(1-30)Online publication date: 4-Oct-2023
https://dl.acm.org/doi/10.1145/3610065

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