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@article{206600,
        author = {Vishakh K T and Akshitha N R and Shradda},
        title = {AI-Driven Instagram Analytics: InstaFlow an Intelligent Content Performance Evaluation Platform},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {106-112},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=206600},
        abstract = {This project focuses on developing an AI-powered analytics platform for Instagram content performance evaluation. The system analyzes various types of posts such as reels, images, and carousels to provide insights into engagement, reach, and audience behavior. Using machine learning and sentiment analysis, the platform evaluates captions, hashtags, and user interactions to identify trends and predict future performance. The system includes real-time analysis of captions and comments to determine emotional tone, helping users optimize their content strategy. Visual dashboards present insights such as content growth, engagement flow, and niche performance. The objective is to assist content creators, influencers, and marketers in making data-driven decisions to maximize reach and engagement on Instagram.},
        keywords = {Instagram Analytics, Artificial Intelligence, Machine Learning, Sentiment Analysis, Large Language Models, Langflow, Astra DB, social media, Content Performance, InstaFlow.},
        month = {July},
        }