Finding Emotion in Image Descriptions: Crowdsourced Data
Morgan Ulinski, Victor Soto Martinez, Julia Hirschberg · 2012
This dataset contains 660 images, each annotated with descriptions and mood labels. The images were originally created by users of the WordsEye text-to-scene system (https://www.wordseye.com/) and were downloaded from the WordsEye gallery. For each image, we used Amazon Mechanical Turk to obtain: (a) a literal description that could function as a caption for the image, (b) the most relevant mood for the picture (happiness, sadness, anger, surprise, fear, or disgust), (c) a short explanation of why that mood was selected. We published three AMT HITs for each picture, for a total of 1980 captions, mood labels, and explanations. This data was used for the machine learning experiments presented in: Morgan Ulinski, Victor Soto, and Julia Hirschberg. Finding Emotion in Image Descriptions. In Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining, WISDOM '12, pages 8:1-8:7. Please cite this paper if you use this data.