How to perform Sentiment Analysis and Text Classification with OpenAI API
Sentiment analysis and text classification are two important natural language processing (NLP) tasks. Sentiment analysis is the task of determining the sentiment of a piece of text, such as whether it is positive, negative, or neutral. Text classification is the task of assigning a label to a piece of text, such as a product review, a news article, or a social media post.
Why might you need this? This is important for various industries like marketing, financial, and customer relations. It's important for users to be able to decide quickly whether a message is positive or negative and decide the potential impact to financial instruments, marketing campaigns, and more.
How might you do this, you may ask? The OpenAI API provides endpoints that can be used to perform sentiment analysis and text classification. These endpoints use large language models, such as GPT-3.5 and GPT 4, to analyze the text and determine its sentiment or label.
In this blog post, we will show you how to use the OpenAI API to perform sentiment analysis and text classification. We will also include the source code used in the video as a free download!
