Automatic Detection of Relevant Information, Predictions and Forecasts in Financial News through Topic Modelling with Latent Dirichlet Allocation

This work proposes a novel Natural Language Processing (NLP) system to assist investors in the detection of relevant financial events in unstructured textual sources by considering both relevance and temporality at the discursive level.