Stance and Gender Detection in Spanish Tweets

José-Ángel González, Lluís-F. Hurtado, Ferran Pla

Abstract: In this paper, we present a deep learning based system for the user profiling and stance detection tasks in Twitter. Stance detection consists in automatically determining from text whether the author is in favor of a given target, against this target, or whether neither inference is likely. The proposed system assembles Convolutional Neural Networks and Long Short-Term Memory neural networks. We use this system to address, with minor changes, both problems. We explore embeddings and one-hot vectors at character level to select the best tweet representation.