The problem TwitterInsight solves

TwitterInsight solves the challenge of analyzing large volumes of Twitter data manually, which is time-consuming and inefficient. By automating sentiment analysis, identifying feedback, and visualizing trends, it empowers users to extract valuable insights quickly and effectively. This enables businesses to make data-driven decisions, understand customer sentiment, and track market trends with ease. Additionally, the integration of AI and Snap-Ins enhances the platform's capabilities, providing advanced analytics and customization options for users. Overall, TwitterInsight revolutionizes Twitter data analysis, making it more accessible, insightful, and actionable for a wide range of users.

Challenges we ran into

Incorporating Snap-Ins into the project proved challenging due to its complexity and learning curve. We had to invest time and effort in understanding the Snap-In platform and its various components to ensure seamless integration and functionality.

We faced delays and disruptions due to problems with the Twitter API. In particular, there were instances where the API key version was downgraded, leading to compatibility issues and temporary setbacks in data retrieval and analysis.

Selecting the right AI model for sentiment analysis and question answering posed a challenge. We needed to evaluate multiple models and APIs to find the most suitable ones that provided accurate and reliable results for our application's requirements.