Abstract
Since the introduction of social media platforms, researchers have investigated how the use of such media affects adolescents’ well-being. Thus far, findings have been inconsistent. The aim of our interdisciplinary project is to provide a more thorough understanding of these inconsistencies by investigating who benefits from social media use, who does not and why it is beneficial for one yet harmful for another. In this presentation, we explain our approach to combining social scientific self-report data with the use of deep learning to analyze personal Instagram archives
Original language | English |
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Title of host publication | ICMI '20 Companion: Companion Publication of the 2020 International Conference on Multimodal Interaction |
Place of Publication | New York |
Publisher | Association for Computing Machinery |
Pages | 523 |
Number of pages | 1 |
ISBN (Print) | 978-1-4503-8002-7 |
DOIs | |
Publication status | Published - 28 Oct 2020 |
Event | 22nd ACM International Conference on Multimodal Interaction: Workshop on Bridging Social Sciences and AI for Understanding Child Behavior - Utrecht, Netherlands Duration: 25 Oct 2020 → 29 Oct 2020 http://icmi.acm.org/2020/ |
Conference
Conference | 22nd ACM International Conference on Multimodal Interaction: Workshop on Bridging Social Sciences and AI for Understanding Child Behavior |
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Abbreviated title | ACM ICMI WoCBU |
Country/Territory | Netherlands |
City | Utrecht |
Period | 25/10/20 → 29/10/20 |
Internet address |