  We use a method based on machine learning, big-data analytics, and network
theory to process millions of messages posted in Twitter to predict election
outcomes. The model has achieved accurate results in the current Argentina
primary presidential election on August 11, 2019 by predicting the large
difference win of candidate Alberto Fernandez over president Mauricio Macri; a
result that none of the traditional pollsters in that country was able to
predict, and has led to a major bond market collapse. We apply the model to the
upcoming Argentina presidential election on October 27, 2019 yielding the
following results: Fernandez 47.5%, Macri 30.9% and third party 21.6%. Our
method improves over traditional polling methods which are based on direct
interactions with small number of individuals that are plagued by ever
declining response rates, currently falling in the low single digits. They
provide a reliable polling method that can be applied not only to predict
elections but to discover any trend in society, for instance, what people think
about climate change, politics or education.
