This chapter describes the basic mechanics for building a forecasting model that uses as input sentiment indicators derived from textual data. In addition, as we focus our target of predictions on financial time series, we present a set of stylized empirical facts describing the statistical properties of lexicon-based sentiment indicators extracted from news on financial markets. Examples of these modeling methods and statistical hypothesis tests are provided on real data. The general goal is to provide guidelines for financial practitioners for the proper construction and interpretation of their own time-dependent numerical information representing public perception toward companies, stocks’ prices, and financial markets in general.

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The Zipf distribution also known as scale-free distribution or discrete Pareto distribution, is the particular case of Power Law distribution with support the strictly positive integers. It is a one-parameter distribution with a linear behaviour in the log-log scale. In this paper the Zipfian distribution is generalized by means of the Marshall-Olkin transformation. The new model has more flexibility to adjust the probabilities of the first positive integer numbers while keeping the linearity of the tail probabilities. The main properties of the new model are presented, and several data sets are analyzed in order to show the gain obtained by using the generalized model.

The “Advanced Big Data Training School for Life Sciences” took place during September 3-7, 2018, organized by the Data Management Group (DAMA-UPC) at the Technical University of Catalonia (UPC) in Barcelona, Spain. It is the follow-up training school of the first “Big Data Training School for Life Sciences”, held in Uppsala, Sweden, in September 2017, which was defined and structured at the “Think Tank Hackathon”, held in Ljubljana, Slovenia, in February 2018. The aim of this training school was to get participants acquainted with emerging Big Data processing techniques in the field of Computational Biology and Bioinformatics.This article explains in detail the development of the training school, the covered contents and the interaction of the participants within and out of the training event by the student, organizer and lecturer perspective.