As government agencies try to adopt AI to accelerate their digital transformation, there is a need for services that enable faster application of AI to common scenarios, without requiring any machine learning expertise. Most any application can be made more "intelligent". The opportunity is to determine where the greatest impact. Agency websites and applications can be easily modernized in order to create more inclusive, accessible and intelligent services for citizens.
Applied AI Services, built on top of Azure Cognitive Services with additional task-specific AI models and business logic to solve common problems organizations encounter, such as sentiment analysis. Without having AI expertise, development teams can build AI solutions that will identify key terms and phrases, understand sentiments, and build conversational interfaces into applications. Annotate, train, evaluate, and deploy customizable models using Cognitive Service for Language without machine-learning expertise.
Risks
An AI system includes not only the technology, but also the people who will use it, the people who will be affected by it, and the environment in which it is deployed. Read the transparency note for sentiment analysis to learn about responsible AI use and deployment in your systems.
Rationale
Sentiment analysis and opinion mining are features offered by Azure Cognitive Service for Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. These features help you find out what people think of your brand or topic by mining text for clues about positive or negative sentiment, and can associate them with specific aspects of the text.
- Analyze positive and negative sentiment in social media, customer reviews, and other sources to get a pulse on your brand.
- Improve citizen experience by monitoring social media and call centers
- Extracts and labels relevant medical information from unstructured texts
As-Is
Sentiment analysis and opinion mining are features offered by Azure Cognitive Service for Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. These features help you find out what people think of your brand or topic by mining text for clues about positive or negative sentiment, and can associate them with specific aspects of the text.
Business Process Model
Sentiment analysis and opinion mining are two ways of detecting positive and negative sentiment. Using sentiment analysis, you can get sentiment labels (such as "negative", "neutral" and "positive") and confidence scores at the sentence and document-level. Opinion Mining provides granular information about the opinions related to words (such as the attributes of products or services) in the text.
How to perform sentiment analysis and opinion mining - Azure Cognitive Services | Microsoft Docs