Explores the analysis of mood expressed on Twitter using longitudinal data and text analysis tools, emphasizing the importance of considering biased data.
Covers the principles and methods of clustering in machine learning, including similarity measures, PCA projection, K-means, and initialization impact.
Delves into the 'digital turn' in history, examining historical research using digitized newspapers and exploring text reuse, word embeddings, and data visualization.
