SentiCart: Cartography and Geo-contextualization for Multilingual Visual Sentiment

Where in the world are pictures of cute animals or ancient architecture most shared from? And are they equally sentimentally perceived across different languages? We demonstrate a series of visualization tools, that we collectively call SentiCart, for answering such questions and navigating the landscape of how sentiment-biased images are shared around the world in multiple languages. We present visualizations using a large-scale, self-gathered geodata corpus of >1.54M geo-references coming from over 235 countries mined from >15K visual concepts over 12 languages. We also highlight several compelling data-driven findings about multilingual visual sentiment in geo-social interactions.

• Human-computer interaction and visualization