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Bio
Claudia Wagner is a full professor (W3) for Applied Computational Social Sciences at RWTH Aachen University and the Scientific Director of the department Computational Social Science at GESIS - Leibniz Institute for the Social Sciences. Before that, she was a W1 professor for Data Science at the University Koblenz-Landau and the team lead of team Data Science. Wagner received her Ph.D. from the Graz University of Technology in 2013. Before that, she conducted several international research internships, among others at HP labs (Social Computation Lab), Xerox PARC (Augmented Social Cognition Lab), and the Open University (Knowledge Media Institute). To date, she has been awarded substantial research funding either as a PI or co-PI, was awarded a DOC-fFORTE fellowship from the Austrian Academy of Sciences, and received four best paper awards at international conferences (SocialCom 2012, ICWSM 2014, WebSci 2015, and ESWC 2010). She has published full papers in top tier conferences (e.g., WWW, ICWSM, Web Science) and high-impact journals (e.g., IEEE Intelligent System Journal, EPJ Data Science).
Wagner organizes interdisciplinary training events for early career researchers (e.g. the CSS methods Summer School) and coordinates the development of new data collection and analysis instruments for digital trace data. Wagner is also an Advisory Board Member of NRW Graduate School Digital Society, a Steering Committee Member of International AAAI Conference on Web and Social Media and a Steering Committee Member of International Conference on Social Networks Analysis, Management and Security.
Research Interests
Papers共 125 篇Author StatisticsCo-AuthorSimilar Experts
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Data Mining and Knowledge Discoverypp.1-25, (2024)
Web Science Conferencepp.94-102, (2024)
PERSPECTIVES ON PSYCHOLOGICAL SCIENCEpp.17456916231214460-17456916231214460, (2024)
Zehui Yu,Indira Sen,Dennis Assenmacher,Mattia Samory, Leon Fröhling, Christina Dahn,Debora Nozza,Claudia Wagner
CoRR (2024)
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CoRR (2023)
COMMUNICATION METHODS AND MEASURES (2023)
Quant. Sci. Stud.no. 1 (2023): 128-152
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