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Results for "media bias"

How MBZUAI’s first NLP Ph.D. graduate is bringing bias to light

MBZUAI ·

Muhammad Arslan Manzoor became MBZUAI's first NLP Ph.D. graduate, focusing his research on media bias under Professor Preslav Nakov. His thesis, 'MGM,' explored using audience overlap graphs to predict the factuality and bias of news media, an approach that differs from traditional textual analysis. Manzoor's work aims to improve the efficiency of media profiling in real-time by leveraging relationships captured in media graphs. Why it matters: This research offers innovative methods for identifying bias in news, which is crucial for promoting informed social discourse and combating disinformation in the region.

Tackling media bias with NLP

MBZUAI ·

MBZUAI student Zain Muhammad Mujahid is researching methods to detect media bias using NLP and LLMs. His approach profiles bias across media outlets using LLMs like ChatGPT to predict bias based on 16 identifiers. The research aims to develop a tool that instantly provides a bias profile for a given media URL. Why it matters: This research has the potential to combat misinformation and enhance media literacy in the region by providing tools to identify biased reporting, and it is expanding to Arabic and other languages.

Decoding the news: a new application to identify persuasion techniques in the media

MBZUAI ·

MBZUAI Professor Preslav Nakov has developed FRAPPE, an interactive website that analyzes news articles to identify persuasion techniques. FRAPPE helps users understand framing, persuasion, and propaganda at an aggregate level, across different news outlets and countries. Presented at EACL, FRAPPE uses 23 specific techniques categorized into six broader buckets, such as 'attack on reputation' and 'manipulative wording'. Why it matters: The tool addresses the increasing difficulty in discerning factual information from disinformation, providing a means to identify biases in news media from different countries.

The war on fake news can be won

MBZUAI ·

MBZUAI Professor Preslav Nakov believes AI can outpace human fact-checkers in detecting fake news by analyzing language and sentence structure. AI systems can identify common sources of fake news and flag domains for blocking. Nakov's research focuses on disinformation, fact checking, and media bias detection. Why it matters: AI-driven solutions for combating fake news could help mitigate the spread of misinformation and its impact on society, especially in the Arabic-speaking world.