GitHub repository: L-Unions/WASSA-2018-Implicit-Emotion-Shared-Task-Data
Primary language: Python
Created: 2018-07-08T09:06:04Z
Description: ou will be given a tweet from which a certain emotion word is removed. That word is one of the following: "sad", "happy", "disgusted", "surprised", "angry", "afraid" or a synonym of one of them. Your task is to predict the emotion the excluded word expresses: Sadness, Joy, Disgust, Surprise, Anger, or Fear.  With this formulation of the task, we provide data instances which are likely to express an emotion. However, the emotion needs to be inferred from the causal description, which is typically more implicit than an emotion word. We therefore presume that successful systems will take into account world knowledge in a structured or statistical manner.  Examples are:  "It's [#TARGETWORD#] when you feel like you are invisible to others." "My step mom got so [#TARGETWORD#] when she came home from work and saw that the boys didn't come to Austin with me." "We are so #[#TARGETWORD#] that people must think we are on good drugs or just really good actors." The shared task consists of the challenge to build a model which recognizes that [#TARGETWORD#] corresponds to sadness ("sad") in the first two examples and with joy ("happy") in the third.