A python package for flexible and transparent sentiment analysis.
Project description
Asent: Fast, flexible and transparent sentiment analysis
Inspired by Vader, made using SpaCy, transparent from the start.
Simple Example
The following shows a simple example of how you can quickly apply sentiment analysis using asent. For more on using asent see the usage guides.
import spacy
import asent
# load spacy pipeline
nlp = spacy.load("da_core_news_lg")
# add the rule-based sentiment model
nlp.add_pipe("asent_da_v1")
# try an example
text = "jeg er ikke længere sur. 👿"
doc = nlp(text)
# visualize the results
asent.visualize(doc)
📖 Documentation
Documentation | |
---|---|
📚 Usage Guides | Guides and instructions on how to use asent and its features. |
📰 News and changelog | New additions, changes and version history. |
🎛 [Documentations] | The detailed reference for augmenty's API. Including function documentation |
💬 Where to ask questions
Type | |
---|---|
🚨 FAQ | FAQ |
🚨 Bug Reports | GitHub Issue Tracker |
🎁 Feature Requests & Ideas | GitHub Issue Tracker |
👩💻 Usage Questions | GitHub Discussions |
🗯 General Discussion | GitHub Discussions |
🎓 Citing asent
If you use this library in your research, please cite it using:
@inproceedings{asent2021,
title={Asent: Fast, flexible and transparent sentiment analysis},
author={Enevoldsen, Kenneth and Hansen, Lasse},
year={2021}
}
Project details
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