Detecting Negative Emotions during Social Media Use on Smartphones


Photo by Oleg Magni on Unsplash


Emotions are integral to the social media user experience; we express our feelings, react to posted content and communicate with emoji. This may lead to emotional contagion and undesirable behaviors such as cyberbullying and flaming. Nearly real-time negative emotion detection during the use of social media could mitigate these behaviors, but existing techniques rely on corpora of aggregated user-generated data - posted comments or social graph structure. This paper explores how live data extracted from smartphone sensors can predict binary affect, valence and arousal during the typical social media tasks of browsing content and chatting. Results show that momentary emotion can be predicted, using features from screen touches and device motions, with peak F1-scores of 0.86, 0.86, 0.88 for affect, valence and arousal.



Mintra Ruensuk

Mintra Ruensuk is a second year PhD student in the Graduate School of Creative Design Engineering at UNIST. She holds a MSc in Computer Science from AIT, Thailand. Mintra's research focus includes social computing, affect detection, and software engineering.


Hyunmi Oh

Hyunmi Oh is a second year Master student in Department of Human Factors Engineering at UNIST. She has a Bachelor of Engineering in Digital Imaging and an interdisciplinary degree in Entrepreneurship from Chung-Ang University. She is interested in tangible interactions and assistive technologies.


Eunyong Cheon

Eunyong Cheon a second year Master student in Department of Human Factors Engineering at UNIST. He is currently working on analyzing biometric data of wearable devices.


Hwajung Hong

Hwajung Hong is an Assistant Professor in the department of Communication at Seoul National University. She is interested in design and social computing with a focus on healthcare and accessibility. She leads the DxD (data, interaction, design) lab with the focus on designing systems that empower individuals and crowds toward creativity and connectivity.


Ian Oakley

Ian Oakley is an associate professor at the School of Design and Human Engineering at UNIST. His research focuses on the design, de- velopment and evaluation of multi-modal inter- faces and social technologies.


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