Sentimental Analysis using Azure Cognitive Services

Introduction

In today’s digital age, social media platforms have become a rich source of valuable insights and emotions from people around the world. With its huge user base and real-time nature, Twitter offers a wealth of information waiting to be explored. Understanding the sentiment behind your tweets can provide valuable insight into public opinion, customer feedback, and market trends.

To harness this wealth of emotional data, we embarked on a journey to harness the power of Azure Cognitive Services. Leverage the power of Azure to combine the Twitter API with a powerful data processing pipeline to collect, pre-process, and store tweets in Azure Data Lake Storage Gen2 (ADLS Gen2). This allows you to efficiently process large amounts of Twitter data and prepare it for sentiment analysis.

After laying the groundwork, leverage the power of Azure Functions, a serverless computing service, to apply cognitive text analytics to stored data. Azure Functions offers a scalable, event-driven architecture that is ideal for processing and analyzing Twitter data at scale. Leverage Azure Functions to automate sentiment analysis processes and process tweets in real-time or in batches depending on your needs.

The core of our analytics lies in Azure Cognitive Services, specifically the Text Analytics API, which provides comprehensive natural language processing capabilities. The Sentiment Analysis feature of the Text Analytics API gives insight into your…