The correct answer is D. Recurrent Neural Network (RNN).
RNNs are a type of artificial neural network that are well-suited for tasks that involve sequential data, such as natural language processing. They are able to learn long-range dependencies between words in a sentence, which is important for tasks like sentiment analysis.
Linear regression is a statistical method that is used to model the relationship between two or more variables. It is a simple and easy-to-understand algorithm, but it is not well-suited for tasks that involve sequential data.
Support vector machines (SVMs) are a type of machine learning algorithm that are used for classification and regression tasks. They are able to learn complex relationships between data points, but they are not as well-suited for tasks that involve sequential data as RNNs.
Naive Bayes is a probabilistic machine learning algorithm that is used for classification tasks. It is a simple and easy-to-understand algorithm, but it is not as accurate as RNNs for tasks like sentiment analysis.
In conclusion, RNNs are the most commonly used machine learning algorithm for natural language processing (NLP) tasks like sentiment analysis. They are able to learn long-range dependencies between words in a sentence, which is important for tasks like sentiment analysis.