Tutorial on July 17, 2023
Link to the tutorial: https://propaganda.math.unipd.it/ic2s2-tutorial/
Appeal to values is fundamental in mass persuasive communication. Appropriate framing may enable effective communication campaigns designed to promote vaccination uptake or pro-environmental attitudes, or can be employed to detect propaganda attempts. In this tutorial, we give an overview of how the basic human and moral values are interpreted and quantified according to the psychological literature, how they can be assessed from user generated data, and how they may be employed in persuasion and propaganda identification.
Kyriaki Kalimeri, ISI Foundation, Italy
Kyriaki Kalimeri is a researcher at the ISI Foundation, Turin, Italy. She received her PhD in Brain and Cognitive Sciences from the University of Trento and her Diploma in Electrical and Computer Engineering from the Technical University of Crete. Her research lies at the intersection of computational social science, social media analysis, and machine learning. The focus is on the automatic prediction of psychological characteristics and moral worldviews from digital data, employing machine learning techniques, translating data into insights for the design of effective communication strategies. Since 2019 she co-organizes the Data for theWellbeing of the Most Vulnerable workshop at ICWSM.
Giovanni Da San Martino, University of Padova, Italy Giovanni Da San Martino is Assistant Professor at the University of Padova. His research interests are at the intersection of machine learning and natural language processing. He served as general chair for CLEF’22 and organised several events around the topic of disinformation: workshops, shared tasks and tutorials (IJCAI'20, EMNLP'20, WWW'22).
Oscar Araque, Universidad Politécnica de Madrid (Technical University of Madrid, UPM)
Oscar Araque is currently Assistant Professor at Universidad Politécnica de Madrid (UPM). His research interest includes the application of machine-learning techniques for natural language processing. In addition, his research interests lie in introducing specific domain knowledge into machine learning systems to enhance sentiment and emotion analysis techniques and their applications to new domains, such as radicalization narratives. His work has received four distinguished prizes: Most Cited Scientific Paper Award 2020 by the Universidad Politécnica de Madrid, Prize for the Most Cited Scientific Article Originating from a UPM Doctoral Thesis 2021, ISDEFE Award for the Best Doctoral Thesis in Security and Defense 2020, and Extraordinary Doctoral Thesis Award - ETSIT UPM 2022.
Yelena Mejova, ISI Foundation, Italy
Yelena Mejova is a Senior Research Scientist at the ISI Foundation, Turin, Italy, working in the area of Data Science for Social Impact and Sustainability. Her research concerns the use of social media in health informatics, especially in lifestyle diseases, as well as for tracking political speech and other cultural phenomena. Previously as a scientist at the Qatar Computing Research Institute, Yelena was a part of the Social Computing Group working on computational social science, especially as applied to tracking real-life health signals. She was the general co-chair of ICWSM’22 and currently, she is the co-Editor-in-Chief of EPJ Data Science.
- Human and moral values
- Propaganda, persuasion & coordinated behaviour
- Controversy detection