This course explores the intersection of computing and social sciences, focusing on computational techniques for analyzing and understanding social behavior, online interactions, and collective intelligence. The course is structured around student-led discussions of scientific articles and the application of computational methods in social computing. Students will engage in critical analysis of recent research and develop skills in implementing computational approaches for social data analysis. The course consists of four introductory lectures followed by student-led discussions of research articles. The first two sessions will provide an overview of social computing and the computational techniques commonly used in the field. In subsequent sessions, students will present selected research papers, followed by group discussions. The following topics wil be explored in this course: (i) Data Characterization: Statistics and Probability (basic concepts).(ii) Social Network Analysis: Basic concepts in graphs, Graph models, Epidemiological models. (iii) Machine Learning Models (Regression, NLP, Transformers): Word Embeddings; Topic Analysis (LDA, BerTopic); Sentiment Analysis. By the end of this course, students will be able to: 1. Understand fundamental concepts in social computing and its interdisciplinary applications. 2. Critically analyze and discuss scientific papers related to social computing. 3. Apply computational techniques to social datasets. 4.Develop insights into current research trends and challenges in the field.

VISITING PROFESSOR Ana Paula Couto da Silva is a Full Professor in the Department of Computer Science at the Universidade Federal de Minas Gerais (UFMG). She holds a degree in Mathematics with a Bachelor's in Informatics from the Universidade Federal de Juiz de Fora (1999) and a Master's and Ph.D. in Systems and Computing Engineering from the Universidade Federal do Rio de Janeiro, with an emphasis on Computer Networks, in 2001 and 2006, respectively. In 2005, she undertook a Ph.D. internship at IRISA/France. In 2007 and 2008, she was a Postdoctoral Fellow at IRISA/France and the Politecnico di Torino, respectively. In 2010 and 2011, she was a visiting researcher at the Politecnico di Torino, Italy. In 2016 and 2017, she was a visiting professor at the same institution. Between 2009 and 2013, she was a professor in the Department of Computer Science at the Universidade Federal de Juiz de Fora. She has published over 40 journal articles and 100 conference papers. She was a collaborating researcher in five projects funded by the European Community, in addition to coordinating or participating in more than 20 projects in Brazil. Currently, she is part of the executive committee and also serves as a Principal Investigator at the Brazilian Innovation Center for Artificial Intelligence in Health (CI-IA Saude). Her main research interests include computational systems modeling, Markovian reward models, numerical methods for solving Markovian processes, complex network modeling, and social computing. Lecture 1 (3h) Introduction to Social Computing: motivation, main research topics, and computational tools. Lecture 2 (3h) Basic concepts on (i) Data Characterisation; (ii)Social Network Analysis: Basic concepts in graphs, Graph models, Epidemiological models. (iii) Machine Learning Models (Regression, NLP, Transformers): Word Embeddings; Topic Analysis (LDA, BerTopic); Sentiment Analysis. Lecture 3 (3h) Seminar Student-led readings and discussions based on the selected research paper. Lecture 4 (3h) Seminar Student-led readings and discussions based on the selected research paper. Lecture 5 (3h) Research project discussion. List of the papers: To be announced.

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P.D.1-1 - Gennaio