Text mining and Natural Language Processing for Computational Social Sciences
The second school of Social ComQuant’s summer school series focuses on methods for analyzing and modeling textual data (e.g. text mining, text classification, information extraction, sentiment analysis, latent semantic models, NLP, event extraction).

You can also click the link to get more information about the project summer school.
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Title: Data Analysis and Visualization

Lecturer: Dr. N. Gizem Bacaksizlar Turbic
Title: Text Classification: Emotion Detection as a Case Study

Lecturer: Dr. Malak Abdullah
Title: Hands-on Introduction to ML with Scikit-learn

Lecturer: Dr. Arnim Bleier
Title: Network Theory Introduction and Analysis

Lecturer: Dr. Michele Tizzoni
Title: Topic Modelling in R Studio

Lecturer: Dr. Ayşe Deniz Lokmanoğlu
Title: Towards "Fair" NLP Models: An Overview of Recent Bias Detection and Mitigation Strategies

Lecturer: Dr. Gözde Gül Şahin
Title: Text Representation Learning

Lecturer: Dr. André Panisson
Title: Applying NLP & ML for CSS: Case Studies in Public Health

Lecturer: Dr. Yelena Mejova
Title: Regular Expressions

Lecturer: Dr. Ali Hürriyetoğlu
Participants presenting their group projects at the end of the summer school.


Behavioral Digital Trace Data in Response to the COVID-19 Pandemic
The main topic of the 1st Social ComQuant Summer School will be the analysis of behavioral digital trace data. Digital traces such as social media posts, search engine queries, mobile phone records, and co-purchases are increasingly allowing social and computational scientists the analysis of human behavior at high spatial and temporal resolution. The COVID-19 pandemic will provide the context of the summer school. Public health advice, stay-at-home orders, and self-imposed limitations have dramatically changed human behaviors on a global scale. For the first time in an epidemic, changes in human behavior have been monitored through digital platforms in real-time. Digital trace data has provided epidemiologists, public health officials, and social scientists with new tools to study the impact of interventions against the virus and how society is changing during the course of the pandemic.

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Title: Tracking Food Insecurity in Near Real-Time: From Data Collection to Predictive Modeling and Back

Lecturer: Dr. Elisa Omodei
Title: Machine Learning Applications During COVID-19

Lecturer: Dr. Maimuna Majumder
Title: Digital Epidemiology Lab

Lecturer: Dr. Marcel Salathe
Title: Data to Fight COVID-19 Pandemic and Where to Find Them

Lecturer: Dr. Nicolo Gozzi
Title: Harnessing Facebook Surveys During the COVID-19 Pandemic

Lecturer: Dr. Daniela Perrotta
Title: Epidemic Modeling

Lecturer: Dr. Nicola Perra
Title: Google Mobility Data

Lecturer: Dr. Laetitia Gauvin
Title: The Politicization of Medical Preprints Online During the Early Stages of COVID-19 pandemic - Deconstructing the Study

Lecturer: Dr. Aleksandra Urman
Title: Collective Phenomena oin Socio-Technical Systems: Modeling and Analysis

Lecturer: Dr. Manlio De Domenico
Title: Network Theory and COVID-19

Lecturer: Dr. Sam V. Scarpino