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Browsing Visual Sentiment Datasets Using Psycholinguistic Groundings

  • Marc A. KastnerEmail author
  • Ichiro Ide
  • Yasutomo Kawanishi
  • Takatsugu Hirayama
  • Daisuke Deguchi
  • Hiroshi Murase
Conference paper
  • 11 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11962)

Abstract

Recent multimedia applications commonly use text and imagery from Social Media for tasks related to sentiment research. As such, there are various image datasets for sentiment research for popular classification tasks. However, there has been little research regarding the relationship between the sentiment of images and its annotations from a multi-modal standpoint. In this demonstration, we built a tool to visualize psycholinguistic groundings for a sentiment dataset. For each image, individual psycholinguistic ratings are computed from the image’s metadata. A sentiment-psycholinguistic spatial embedding is computed to show a clustering of images across different classes close to human perception. Our interactive browsing tool can visualize the data in various ways, highlighting different psycholinguistic groundings with heatmaps.

Keywords

Visual sentiment Psycholinguistics Visualization 

Notes

Acknowledgments

Parts of this research were supported by the MEXT, JSPS KAKENHI 16H02846, and a joint research project with NII, Japan.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Graduate School of InformaticsNagoya UniversityNagoyaJapan
  2. 2.Institute of Innovation for Future SocietyNagoya UniversityNagoyaJapan
  3. 3.Information Strategy Office, Nagoya UniversityNagoyaJapan

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