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A positive sentiment analysis
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Analyzing the emotion of the text
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A negative sentiment analysis
Inspiration - The reason behind it!
Sentiment analysis is a powerful marketing tool that enables product managers to understand customer emotions in their marketing campaigns. It is an important factor when it comes to product and brand recognition, customer loyalty, customer satisfaction, advertising and promotion success, and product acceptance. Sentiment analysis is extremely useful in social media monitoring as it allows us to gain an overview of the wider public opinion behind certain topics. Being able to quickly see the sentiment behind everything from forum posts to news articles means being better able to strategize and plan for the future.
What it does?
You are required to provide text or a Uniform Resource Locator and, it will analyze, create a sentiment/emotion report. It is capable of analyzing the mood of the text like sadness, joy, fear, disgust, and anger. It can tell you whether the text meaning is positive, neutral, or negative.
How do we build it?
We started creating a server and linking it with IBM-NLU as IBM provides it free of any charges. It is a Node.js-based server capable of handling routes effectively. Then we created a React application and installed Bootstrap for the UI. GET & POST requests are made from both ends to make a seamless flow of data exchange.
Challenges we ran into:
1) Connecting our application with IBM-NLU as we have never used it before. 2) Creating routes in the server and sending/handling the requests. 3) Optimizing the application for production-ready code.
Accomplishments that we're proud of:
We can perform the sentiment analysis of texts/URLs efficiently. The project is one of the first MERN projects that we have made. We have tried to optimize the code to make it production-ready.
What we learned?
1) We learned how to use IBM-NLU. 2) How to create a full-stack MERN web application. 3) How to link frontend with backend. 4) How to handle routes. 5) How to fetch API. 6) How to use environment variables.
What's next for Sentiments Analyzer?
We will enhance its UI capabilities and make it more responsive. We will also add more features provided by IBM-NLU.
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