Abstract
This study investigates the relationship between memory, emotions evoked through smartphone photographs, and smartphone attachment. Specifically, it examines the effects of the level autobiographical memory is induced through photos on smartphone attachment and how this relationship is influenced according to the emotions induced through these photos. An experiment was conducted on 17 individuals 22-37 years old. Each participant was asked to select a photo from their smartphone that caused the strongest emotions and was asked to write a memory induced by the photo in about 200 characters. The participant then measured their emotions for the selected photo and responded to a questionnaire about memory and mobile attachment. As a result, it was confirmed that valence regulates the relationship between autobiographical memory and smartphone attachment. In particular, it has been shown that when emotions are unpleasant, they induce strong smartphone attachment with higher levels of autobiographical memory.
Original language | English |
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Title of host publication | Proceedings of MUM 2022, the 21st International Conference on Mobile and Ubiquitous Multimedia |
Editors | Tanja Doring, Susanne Boll, Ashley Colley, Augusto Esteves, Joao Guerreiro |
Publisher | Association for Computing Machinery |
Pages | 292-294 |
Number of pages | 3 |
ISBN (Electronic) | 9781450398213 |
DOIs | |
Publication status | Published - 2022 Nov 27 |
Event | 21st International Conference on Mobile and Ubiquitous Multimedia, MUM 2022 - Lisbon, Portugal Duration: 2022 Nov 27 → 2022 Nov 30 |
Publication series
Name | ACM International Conference Proceeding Series |
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Conference
Conference | 21st International Conference on Mobile and Ubiquitous Multimedia, MUM 2022 |
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Country/Territory | Portugal |
City | Lisbon |
Period | 22/11/27 → 22/11/30 |
Bibliographical note
Publisher Copyright:© 2022 Owner/Author.
All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software