Sentiment Analysis of Text
Food for Thought
AI models can determine the sentiment (positive, negative, or neutral) expressed in a given text.
Example
Analyzing customer reviews of a product to gauge overall satisfaction.
Key Questions
- What business processes and tasks require the determination of a sentiment expressed in textual information?
- How does the identified sentiment affect the next steps of the process?
- Whose sentiments are we interested in to improve our offerings, processes, and experiences?
Implementation
Classifying can be achieved with a prompt on a foundation model, particularly a large language model. Here you find how to access a foundation model in SAP BTP to implement a use-case that includes “Sentiment Analysis” as an AI functional capability.
After you have access to a foundation model, you can use this learning journey to implement summarization:
- Prompt LLMs in the generative AI hub in SAP AI Core & Launchpad (the “Sentiment Analylsis” section)