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Enrich Twingly Reviews with Tisane Topic Extraction
Top companies trust Datastreamer to integrate, enrich, join, and apply their web data needs.
About Twingly Reviews
Twingly captures our 15 million reviews per month from all corners of the world.
About Tisane Topic Extraction
Find out the subjects the users are talking about. Classify content by topic. Intelligently deduce geographic region.
Super granular. Supports IPTC, IAB, and Wikidata IDs.
Also known as: theme identification, subject detection, or key topic recognition. Topic extraction determines the dominant topics in the text.
Tisane provides the topics at a document level.
When a particular word has multiple interpretations, the sense of the word must be determined in the current context. For example, Jupiter is a planet and a Roman deity. Whether it's the planet or the deity, depends on the text.
For example, the sentence Juno is the wife of Jupiter refers to the deity. Tisane determines the relevant topics as Roman mythology, supernatural (gods), relationship, and family (since the spousal connection is mentioned).
There are common taxonomy standards that Tisane can provide::
native - native Tisane topic names; based on standard English terms for the topic. The default standard.
Quickly enrich Twingly Reviews with Tisane Topic Extraction with a Datstreamer Pipeline.
Step 1
Start your Pipeline with Twingly Reviews
Web data serves as the foundational input for any data pipeline. Pipelines can be powered by diverse data sources, including datasets from our partner ecosystem, proprietary internal systems, or any externally accessible web data.
Step 2
Add Tisane Topic Extraction to enrich
Datastreamer lets you accelerate your data usage by applying operations like structuring, enriching, joining, and filtering—choose from hundreds of prebuilt, plug-and-play options.
Step 3
That's it! You have just connected Twingly Reviews and Tisane Topic Extraction
Supercharge your data workflows with Datastreamer. Add flexibility to your Pipelines and put an end to the common bottlenecks in handling web data.