| Challenge: | a dataset of 4,000 pieces of art has annotations for emotions evoked in the observer . the dataset can help answer questions about what makes art evocative, how does art convey different emotions, what attributes of a painting make it well liked, and how much does the title impact the affectual response to art. |
| Approach: | They create a dataset of 4,000 western art pieces that has annotations for emotions . they use crowdsourcing to annotate the art for one or more of twenty emotion categories . fear, happiness, love, sadness were the dominant emotions that obtained consistent annotations . |
| Outcome: | The dataset shows that the most popular emotions are fear, happiness, love and sadness . the dataset can be used to develop systems that detect emotions evoked by art . |
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