Al Jazeera enhances Arabic media monitoring accuracy by integrating data from Aligator

Challenge

Al Jazeera's monitoring tools were generating unreliable sentiment analysis and lacked comprehensive data, leading to excessive noise and a lack of context. As a result, teams found it difficult to rely on these insights for making informed PR, product, and editorial choices.

Solution

We developed a robust API for Al Jazeera, transforming how teams analyze audience data. This solution offers a clear view of brand perception based on reliable, real-time data.

Results

Enhanced Accuracy

Significant reduction in false or misleading sentiment readings especially for Arabic media.

Time Efficiency

PR and product teams saved hours previously spent sifting through irrelevant mentions.

Deeper Insights

Producers gained a reliable understanding of brand perception across platforms and regions.

Approach& Key Features

Integrated Data Flow

We combined articles, YouTube comments, and social media posts from Facebook, Instagram, and X into a single system for easy monitoring.

Advanced Filtering

We trained an AI model to filter out the unnecessary noise and highlight only the most valuable and contextually relevant mentions.

Arabic Sentiment Analysis

We designed AI models that accurately detect sentiment in Arabic mentions across all dialects in the region.

“We’ve been struggling with Arabic mentions. Thanks to Aligator’s data, our reports have been more accurate and trustworthy.”

Fahad Abdullah

Al Jazeera, Applications Manager

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