UOBIT @ TAG-it: Exploring a Multi-faceted Representation for Profiling Age, Topic and Gender in Italian Texts

This paper describes our system for participating in the TAG-it Author Profiling task at EVALITA 2020. The task aims to predict age and gender of blogs users from their posts, as the topic they wrote about. Our proposal combines learned representations by RNN at word and sentence levels, Transformer Neural Nets and hand-crafted stylistic features. All these representations are mixed and fed into a fully connected layer from a feed-forward neural network in order to make predictions for addressed subtasks. Experimental results show that our model achieves encouraging performance.