Aspect Based Sentiment Analysis is a compact text analytics solution that helps you to receive structured and detailed insights out of your textual data.
It discovers topics mentioned in the text, attributes each topic with a topic category, and finally extracts sentiment expressed towards these topics.
While text-level sentiment analysis gauges the overall sentiment of the entire text, Topic-level sentiment provides fine-grained information on the author’s attitude towards a specific topic, such as a product, feature, or service aspect.
Select one of the available industry models to extract most relevant topics with industry-specific category and increase sentiment accuracy with model fine-tuned to the use case.
Industry | English | German | Spanish |
---|---|---|---|
E-commerce | ✓ | ✓ | ✓ |
Employee satisfaction | ✓ | ✓ | ✓ |
Hotel | ✓ | ✓ | ✓ |
Restaurant | ✓ | ✓ | ✓ |
Car dealership | ✓ | ✓ | ✓ |
Banking | ✓ | ||
Retail | ✓ | ✓ | ✓ |
Pharma | ✓ | ||
Consumer electronics | ✓ | ✓ |
Leverage Topic Sentiment Extraction via Symanto API to extract precise and structured insights from text
Extract customer opinions and pain points from reviews, complaints, NPS survey and more
Add value to survey solution by extracting structured opinion insights from unstructured open ends
Glean fine-grained opinion insights towards brands and products from online conversations
Check out the supported languages and API Documentation.
You can try our API free of charge, with no obligation.
Contact us today to discuss how our API could help you and your organisation.
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