Added asent to spacy universe (#11078)

* Added asent to spacy universe

* Update addition of asent following correction
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Kenneth Enevoldsen 2022-07-07 06:25:25 +02:00 committed by GitHub
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@ -1120,6 +1120,46 @@
"category": ["pipeline", "models", "training"], "category": ["pipeline", "models", "training"],
"tags": ["pipeline", "models", "transformers"] "tags": ["pipeline", "models", "transformers"]
}, },
{
"id": "asent",
"title": "Asent",
"slogan": "Fast, flexible and transparent sentiment analysis",
"description": "Asent is a rule-based sentiment analysis library for Python made using spaCy. It is inspired by VADER, but uses a more modular ruleset, that allows the user to change e.g. the method for finding negations. Furthermore it includes visualisers to visualize the model predictions, making the model easily interpretable.",
"github": "kennethenevoldsen/asent",
"pip": "aseny",
"code_example": [
"import spacy",
"import asent",
"",
"# load spacy pipeline",
"nlp = spacy.blank('en')",
"nlp.add_pipe('sentencizer')",
"",
"# add the rule-based sentiment model",
"nlp.add_pipe('asent_en_v1')",
"",
"# try an example",
"text = 'I am not very happy, but I am also not especially sad'",
"doc = nlp(text)",
"",
"# print polarity of document, scaled to be between -1, and 1",
"print(doc._.polarity)",
"# neg=0.0 neu=0.631 pos=0.369 compound=0.7526",
"",
"# Naturally, a simple score can be quite unsatisfying, thus Asent implements a series of visualizer to interpret the results:",
"asent.visualize(doc, style='prediction')",
" # or",
"asent.visualize(doc[:5], style='analysis')"
],
"thumb": "https://github.com/KennethEnevoldsen/asent/raw/main/docs/img/logo_black_font.png?raw=true",
"author": "Kenneth Enevoldsen",
"author_links": {
"github": "KennethEnevoldsen",
"website": "https://www.kennethenevoldsen.com"
},
"category": ["pipeline", "models"],
"tags": ["pipeline", "models", "sentiment"]
},
{ {
"id": "textdescriptives", "id": "textdescriptives",
"title": "TextDescriptives", "title": "TextDescriptives",