Datastreamer lets you connect Social Media Sentiment with thousands of the most popular capabilities, so you can accelerate working with web data and focus on your product – no code required.
Working with web data is resource-intensive, slow, and distracting from your product. Companies using Datastreamer are able to accelerate how they work with web data, by using Pipelines to power their workflows.
Pipelines created in the Datastreamer platform simplify how you work with web data, making it faster to ingest, enrich, and deliver insights. Remove complexity from your web data workflows, reduce distractions from your products, and scale effortlessly.
This component is a text-specialized model that extracts the sentiment from English short-form content. This classifier displays the sentiment extracted from the given text. The output would be one of these labels:
Neutral
Positive
Negative
Use Case
This classifier can act as a search filter. For instance, it provides the users the possibility to filter their search and focus on negative or positive content for further analysis.
More use cases of the model would be available when used along with other classifiers. For instance, it could be used to detect the sentiment of the future action (when used in conjunction with the intent classifier) or could also be used to detect sentiment relating to organizations or people (when used in conjunction with the named entity recognition).
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