News

The sixth edition of the CheckThat! Lab concluded successfully, registering participation from 127 teams.

This shared task is to further encourage work on computational propaganda and disinformation detection over Arabic content. 

"News Genre, Framing, and Persuasion Techniques Detection using Multilingual Models" is scheduled to be presented at the17th International Workshop on Semantic Evaluation (SemEval)

Scientists from QCRI participated in Tasks 3 that focus on addressing misinformation by identifying news genre, media framing, and persuasion techniques in news articles...

Tanbih team is co-organizing CheckThat! Lab Shared task at CLEF 2023 on the topic of Checkworthiness, Subjectivity, Political Bias, Factuality, and Authority of News...

Scientists from QCRI published a paper titled: “Assisting the Human Fact-Checkers: Detecting All Previously Fact-Checked Claims in a Document, at EMNLP 2022”.

The aim of the shared task is to build AI models to detect and identify those means or techniques using Arabic tweets as a...

Tanbih’s team publishes on fake news, propaganda, misinformation, and disinformation in online platforms.

The CLEF 2022 CheckThat! Lab is scheduled to take place from September 5-8, 2022, and will focus on advancing the detection of misinformation and...

Team from QCRI joined an international group of researchers in highlighting the automatic identification of harmful content that can be found online.

Tanbih’s team published a new paper studying the importance of modeling the context of the claims made in political debates.

The Social Computing Group at QCRI brought together leading organizations and researchers in the field of data science for the Artificial Intelligence for Collective...

Dr. Preslav Nakov from QCRI commented on media literacy in “The EU Meets The Balkans Forum”.

Dr Preslav Nakov, a principal scientist at QCRI participated in the 17th International Conference on Persuasive Technology.

We are pleased to announce the publication of a significant research paper titled “FANG: leveraging social context for fake news detection using graph representation”...