Strategic AI Roadmap & Sentiment Analysis Platform for USAID

A USAID initiative needed to understand public sentiment within a specific, multilingual region of the Middle East by analyzing social media data from platforms like TikTok, YouTube, and Instagram. They faced significant hurdles: it was unclear which third-party data vendors were reliable, the quality of the data was unknown, and they lacked a technical approach to ingest, translate, analyze, and visualize the information effectively.

The primary objectives were to:

• Conduct a thorough evaluation of available social media data providers to find a reliable data source.
• Perform a comprehensive Exploratory Data Analysis (EDA) to understand the quality, biases, and limitations of the chosen data.
• Develop a proof-of-concept workflow to process the data, including translation and sentiment analysis.
• Build a full-stack prototype application that would allow non-technical analysts to easily search and visualize sentiment trends and language patterns.

Maximum Labs executed a multi-phase solution that combined strategic advisory with hands-on engineering.

First, we conducted an AI Feasibility Advisory, engaging with multiple data vendors and performing a deep EDA. The findings were delivered in a 70-page strategic document that recommended building a custom data acquisition pipeline using RapidAPI, as off-the-shelf solutions were inadequate.

Next, we moved into a Prototype Sprint. We built a robust data pipeline in Python that acquired social media posts and comments, ran them through a translation service, and performed sentiment analysis. The processed comments, along with their sentiment scores, were embedded and stored in a vector database to enable powerful semantic search.

Finally, we developed a full-stack application that served as an interactive dashboard. This platform allowed USAID analysts to search the entire database of comments using natural language, filter by positive or negative sentiment, and view rich, dynamic data visualizations of trending topics and language patterns, providing unprecedented insight into the regional information landscape.