Understanding Emotions in SNS Images From Posters' Perspectives
- Title
- Understanding Emotions in SNS Images From Posters' Perspectives
- Author
- 김상욱
- Keywords
- Image-based emotion analysis; classification; social network service
- Issue Date
- 2020-03
- Publisher
- ACM SAC 2020
- Citation
- SAC '20: Proceedings of the 35th Annual ACM Symposium on Applied Computing, Page. 450-457
- Abstract
- As the popularity of media-based social networking services (SNS), such as Instagram and Snapchat, has increased significantly, a growing body of research has analyzed SNS images in relation to emotional analysis and classification model development. However, these prior studies were based on relatively small amounts of data, where the emotions of images were labeled from viewers' perspectives, not posters' perspectives. Consequently, we analyze 120K images that reflect poster's emotion. We develop color- and content-based classification models by considering: (1) the dynamics of SNS, in terms of the volume and variety of images shared, and (2) the fact that people express their emotions through colors and objects. We demonstrate the comparable performance of our model with models proposed in prior studies and discuss the applications.
- URI
- https://dl.acm.org/doi/10.1145/3341105.3373923https://repository.hanyang.ac.kr/handle/20.500.11754/162004
- ISBN
- 978-1-4503-6866-7
- DOI
- 10.1145/3341105.3373923
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
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