26. Process extracted data

3.1 Conduct sentiment analysis

ChatGPT can perform sentiment analysis on scraped data to generate interpretable insights from unstructured text data. Assume you scraped social mentions of your brand from a social media platform to analyze your audience growth. After you have obtained data and cleaned the collected data, you can instruct ChatGPT to analyze the text data and label it as negative, neutral, or positive (Figure 4).

Figure 4: Demonstrate the process of analyzing and labeling a sample text document

Here’s an example of how you can instruct ChatGPT to perform sentiment analysis:

“Analyze the sentiment of the text: ‘The battery life is also long’.”

ChatGPT’s response to  our query:

Note that the accuracy of sentiment analysis can vary depending on different factors, such as the complexity of the text and context-dependent errors.

3.2 Categorize scraped content

ChatGPT can help categorize scraped data into predefined categories. You can define the categories you want to classify the content into. Here is an example of categorizing content using ChatGPT:

As an example, we want to categorize the following content:

The following is the output for categorizing scraped data with ChatGPT: