Predicting Engagement with Sponsored Content Across Account Types on Instagram

2026-10-05

AI Summary

This study addresses the challenge of accurately predicting user engagement with sponsored content across diverse Instagram account types. Leveraging a large-scale dataset of over 15 million posts, this work proposes an interpretable regression framework that integrates multidimensional account categorization with NLP-based semantic feature extraction. Rather than relying on opaque deep learning paradigms, the approach prioritizes both predictive accuracy and model transparency through the incorporation of a piecewise optimization strategy. Empirical evaluations demonstrate that the proposed model achieves competitive predictive performance while explicitly revealing the key feature mechanisms driving user engagement. Ultimately, this research contributes a high-precision, highly interpretable analytical framework for evaluating marketing effectiveness on social media platforms.

Abstract

In this work we explore how users interact with sponsored content on social media platforms by collecting and analyzing a large-scale dataset of sponsored Instagram posts. To maintain transparency, we favor robust statistical analysis and explainable models over deep learning techniques. Our pipeline categorizes Instagram accounts along multiple dimensions, including audience size and entity type. We complement this with semantic features extracted from post captions and hashtags, and use these elements to train regression models that forecast engagement. We validate our approach on a dataset comprising over 15M Instagram posts authored by over 700K accounts featuring sponsored content. Our analysis shows that per-post engagement is partly predictable and highly optimized when accounts are segmented by entity type or audience tier. Our models achieve competitive predictive power, while remaining fully transparent about which features drive engagement.

Problem

• Sponsored Content
• Engagement Prediction
• Instagram
• Account Types

Innovation

• Sponsored Content
• Engagement Prediction
• Explainable Models
• Semantic Features
• Account Segmentation