First results from Corona Ad hoc survey: peoples' information sources in the crisis

CA-SG researcher Prof. Oliver Quiring and his team conducted an ad hoc survey on peoples’ information sources in times of the crisis. First results indicate that people rely on a mix of very diverse sources to obtain information on the pandemic: In the first days after the outbreak, people intensively used established news media, but also information shared by private contacts and official sources such as research institutions and public authorities. Moreover, the sources people rely on in the corona crisis significantly impacted peoples’ sense of community in the crisis, indicating that the way how information on the pandemic is presented considerably impacts the social cohesion in society.

New research paper: How to Best Predict the Daily Number of New Infections of COVID-19

Our team of CA-SG researchers (Lukas Jürgensmeier M.Sc., Kevin Stowe Ph.D., Prof. Dr. Bernd Skiera, and Prof. Dr. Iryna Gurevych) has just submitted our first research paper related to the Corona crisis. We compare the ability of several data sources, in particular Johns Hopkins University (JHU), Google search data and Twitter data, to predict the official number of new infections of Covid-19 and examine the need to complement the official numbers with additional predictions.

Jonas Pfeiffer receives IBM PhD Fellowship Award

First year PhD student Jonas Pfeiffer was selected to receive a 2020 IBM PhD Fellowship Award. This highly competitive award honors and supports exceptional PhD students in pioneering research areas. It is granted only to 24 researchers worldwide and from Germany Jonas is the only awardee. Jonas Pfeiffer is pursuing his PhD, supervised by Prof. Iryna Gurevych, at the UKP Lab where his focus is on on multi-modal, multi-lingual and multi-task machine learning. Jonas participates on a CA-SG project “Real-Time Multilingual Multi-Modal Twitter Content Analysis for COVID-19 Crisis Response”.

Teaching CA-SG to Computer Science students in SS2020

The department of Computer Science will offer two courses based on the CA-SG topics in SS 2020 to the students of Computer Science. The first course is a lecture “Ethics in Natural Language Processing” taught by Prof. Iryna Gurevych and Dr. Thomas Arnold. The second course is a Text Analytics seminar taught by Dr. Kevin Stowe and Dr. Ivan Habernal.

BMBF funds Lucie Flek to establish an AI research group on Dynamically Social Discourse Analysis

CA-SG researcher Prof. Dr. Lucie Flek receives a grant of over 1 Mil. Euro from the Federal Ministry of Education and Research (BMBF) for establishing an Independent Research Group on her project DynSoDA: Dynamically Social Natural Language Processing for Online Discourse Analysis. The 4-year project is a part of the BMBF support program for young researchers working in the field of Artificial Intelligence.

Inaugural meeting of the "Content Analytics for the Social Good" research initiative

Over 20 faculty members from the three Rhein-Main (RMU) universities hold an inaugural meeting at the Technical University of Darmstadt. They define the corner stones of the long-term strategic partnership in data science with a focus on Natural Language Processing, Computer Vision and Machine Learning and Social Sciences and Humanities.

The primary area of cooperation is supporting critical political-decision making under uncertainty based on big data. We study this in relation to various interactions with four main societal subsystems, such as economics, law, media and science.