A developer has collected 40 product reviews in S3 and a data scientist needs more labeled review data to train models. Which additional data sources are appropriate to augment the dataset? (Choose three.)

The goal is to augment a dataset of product reviews for model training. Therefore, additional data sources should ideally contain similar textual content related to customer sentiment, product feedback, or general product discussion. Email exchanges between customers and customer service agents are highly relevant as they often contain direct feedback, complaints, or questions about products, providing valuable sentiment and topic information. Social media posts mentioning the company or its products are also excellent sources, as they reflect public opinion, sentiment, and discussions about the products. A publicly available corpus of customer reviews directly provides more examples of the target data type, enriching the dataset with diverse review styles and content. A public collection of news articles is less relevant as it typically focuses on general news and may not contain specific product review sentiment. Product sales revenue figures are numerical and do not provide textual review data. Product instruction manuals are descriptive and factual, lacking the subjective sentiment and feedback found in reviews.