Browsing Visual Sentiment Datasets Using Psycholinguistic Groundings
- 11 Downloads
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.
KeywordsVisual sentiment Psycholinguistics Visualization
Parts of this research were supported by the MEXT, JSPS KAKENHI 16H02846, and a joint research project with NII, Japan.
- 1.Jindal, S., Singh, S.: Image sentiment analysis using deep convolutional neural networks with domain specific fine tuning. In: 2015 International Conference on Information Processing (ICIP), pp. 447–451, December 2015. https://doi.org/10.1109/INFOP.2015.7489424
- 2.Jou, B., Chen, T., Pappas, N., Redi, M., Topkara, M., Chang, S.: Visual affect around the world: A large-scale multilingual visual sentiment ontology. ArXiv e-prints 1508.03868 (2015)
- 4.Kim, E., Klinger, R.: A survey on sentiment and emotion analysis for computational literary studies. ArXiv e-prints 1808.03137 (2018)