Understanding emotions in SNS images from posters' perspectives

Junho Song, Kyungsik Han, Dongwon Lee, Sang Wook Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


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.

Original languageEnglish (US)
Title of host publication35th Annual ACM Symposium on Applied Computing, SAC 2020
PublisherAssociation for Computing Machinery
Number of pages8
ISBN (Electronic)9781450368667
StatePublished - Mar 30 2020
Event35th Annual ACM Symposium on Applied Computing, SAC 2020 - Brno, Czech Republic
Duration: Mar 30 2020Apr 3 2020

Publication series

NameProceedings of the ACM Symposium on Applied Computing


Conference35th Annual ACM Symposium on Applied Computing, SAC 2020
Country/TerritoryCzech Republic

All Science Journal Classification (ASJC) codes

  • Software


Dive into the research topics of 'Understanding emotions in SNS images from posters' perspectives'. Together they form a unique fingerprint.

Cite this