Research Summary: Perceive, Refine, Reason: A Calibrated Pipeline for Measuring Indicators in Strategic Visual Communication on Social Media

A new computational pipeline, Perceive, Refine, Reason (PRR), has been developed to enhance the automated analysis of visual content on social media. This system aims to overcome limitations of existing tools by enabling more precise measurement of specific objects, their prominence, and their spatial location within images. PRR integrates vision-language detectors with pixel-level refinement and multimodal large language models to provide auditable measurement instruments for social-scientific research.

Why it matters

The ability to accurately and at scale analyze specific visual elements in social media content provides deeper insights into strategic communication effectiveness. This precision can inform policy, campaign design, and risk assessment by revealing how visual cues are shaping public perception and opinion. Such granular data is crucial for evidence-based decision-making in various sectors that engage with public sentiment.

Key insights

• Visual content significantly influences audience perception and opinion on social media platforms.
• Current automated tools for image analysis often provide coarse, image-level labels or rely on predefined categories, leading to a measurement gap.
• Measuring specific object presence, prominence, and location within images at scale has been challenging.
• The Perceive, Refine, Reason (PRR) pipeline combines natural-language category prompts with pixel-level spatial refinement (via Segment Anything Model) and multimodal Large Language Model arbitration.
• PRR transforms flexible vision-language detectors into auditable measurement instruments for social-scientific research.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2609.14699