Analyze Sentiment from Text

This bot is designed to perform Natural Language Processing using Amazon Comprehend API by simply plugging this bot into an existing or new task. The bot identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; analyzes text using tokenization and parts of speech, and automatically organizes a collection of text files by topic.

This bot can discover the meaning and relationships in text from customer support incidents, product reviews, social media feeds, news articles, documents, and other sources. For example, you can identify the feature that’s most often mentioned when customers are happy or unhappy about your product. The bot will output entities, key phrases, sentiment, and language in a JSON format, which you can use in your application. Key phrase extraction: This bot returns the key phrases or talking points and a confidence score to support that this is a key phrase. Sentiment analysis: This bot returns the overall sentiment of a text (positive, negative, neutral, or mixed). Entity recognition: This bot returns the named entities ("people," "places," "locations," etc.) that are automatically categorized based on the provided text. Language detection: This bot automatically identifies text written in over 100 languages and returns the dominant language with a confidence score to support that a language is dominant.

Key Use Case: Analyze text and apply the results in a wide range of applications including the voice of customer analysis, intelligent document search, and content personalization for web applications. Analyze text and apply the results in a wide range of applications including the voice of customer analysis, intelligent document search, and content personalization for web applications.