Audience Segmentation for Content Relevance

The patent segments the audience into distinct groups based on their treatment of topics. Instead of treating all users interested in a topic as a single homogeneous group, the system divides them into segments with different viewpoints (e.g., for vs. against climate change). This allows the system to preserve viewpoint information by creating separate audience segments that reflect the nuanced perspectives users hold toward topics they interact with.

The patent applies local quality by tailoring content presentation to the specific viewpoint of each user segment. Instead of presenting the same topic-related content to all users, the system customizes content selection based on the particular treatment each audience segment has toward the topic. For example, pro-climate change users receive content supporting climate change initiatives, while anti-climate change users receive content with opposing viewpoints, ensuring content aligns with their specific perspectives.

The patent implements self-service by enabling the system to automatically determine audience segmentation through user feedback and classification models without requiring manual intervention. The system uses machine learning algorithms that continuously learn from user interactions, automatically updating audience segments based on observed behavior patterns. This automated approach reduces the need for complex manual configuration and maintenance while achieving high categorization accuracy.