Instagram Trends Analyzer: Real-Time Extraction and Visualization of Instagram Engagement Metrics

In today’s fast-evolving digital landscape, Instagram plays a central role in communication, branding, and audience engagement. However, identifying trending content manually is time consuming and inefficient. This project introduces the Instagram Trends Analyzer, a Python-based system that automates the extraction, analysis, and visualization of
Instagram data in real-time. Using the Instagram Graph API, the system collects post-level metrics such as URLs, captions, like counts, comment counts, hashtags, and timestamps. The extracted data is stored in CSV format for structured analysis. A Streamlit dashboard is integrated to visualize key engagement trends, including hashtag rankings, post engagement over time, and real-time filtering features. This user friendly interface allows digital marketers, content creators, and social media analysts to make informed decisions quickly without the need for manual tracking. Unlike existing methods that rely on static datasets or
manual reviews, this solution delivers dynamic insights, is scalable for multi-platform extension, and supports future upgrades such as sentiment analysis and influencer identification. The project bridges a critical gap between social media data availability and decision-making in marketing strategies.