Big Data: Computational Analysis of Text

About

This workshop focuses on the application of the supervised and unsupervised texts analysis technique to real-time Twitter messages that can help social researchers to detect social trends or citizens’ attitudes. Participants will learn the very basis of programming in Python and will be able to retrieve tweets with Streaming and Rest APIs of Twitter. In addition, they will learn the mathematical representation of text (BoW, Embeddings), the basis of natural language processing (tokenizing, stemming, lemmatizing, stop words, frequency of words, etc.) and will learn lexicon-based sentiment analysis and topic modelling. The workshop will focus on supervised machine learning applied to unstructured data with different algorithms implemented in Scikit-Learn (naive bayes, logistic regression, support vector machines, etc.) and TensorFlow / Keras (RNN).

Course leader

Carlos Arcila Calderón, PhD - Universidad de Salamanca

Target group

Professionals, Researchers, and Students, who wish to develop high-quality surveys and employ up-to-date statistical methods for survey data analysis. Potential attendees include survey practitioners, marketing professionals, social science students, and researchers.