You must analyze user comments on a global news website to identify the most discussed topics. Comments are written in English and Spanish. Which steps would accomplish this task? (Select the best option.)

The correct approach is to translate Spanish comments into English using an automated translation service and then use a topic-modeling service. This is practical and efficient for multi-language topic extraction. Automated translation services (like Amazon Translate) are designed for this purpose, and topic modeling services (like Amazon Comprehend Topic Modeling) are optimized for identifying themes in large text datasets. Training a language-agnostic word-embedding model is complex and might not yield clear topics without further processing. Training a sequence-to-sequence model for translation is unnecessary when robust, pre-trained services are available. Using a conversational chatbot service for topic extraction is not its primary function and would be inefficient. While neural topic-modeling algorithms exist, using a readily available topic-modeling service after translation is a more straightforward and often equally effective solution for this use case.