Universe

eng_spacysentiment

Simple sentiment analysis using spaCy pipelines

Sentiment analysis for simple english sentences using pre-trained spaCy pipelines

Example

import eng_spacysentiment nlp = eng_spacysentiment.load() text = "Welcome to Arsenals official YouTube channel Watch as we take you closer and show you the personality of the club" doc = nlp(text) print(doc.cats) # {'positive': 0.29878824949264526, 'negative': 0.7012117505073547}
Author info

Vishnu Nandakumar

GitHubvishnunkumar/spacysentiment

Categories pipeline

Submit your project

If you have a project that you want the spaCy community to make use of, you can suggest it by submitting a pull request to the spaCy website repository. The Universe database is open-source and collected in a simple JSON file. For more details on the formats and available fields, see the documentation. Looking for inspiration your own spaCy plugin or extension? Check out the project idea label on the issue tracker.

Read the docsJSON source