revised-stopwords 0.1.2

An optimized stopwords list for sentiment analysis that retains key negations like 'not', 'won't', and 'wouldn't', along with intensity modifiers like 'very' and 'most' to preserve sentiment accuracy.

Revised Stopwords for NLP

Overview

This package provides an optimized stopwords list for sentiment analysis by preserving sentiment-related words that NLTK’s default list would typically remove. By retaining key negations and intensity modifiers, this package ensures that sentiment expressions remain intact, leading to more accurate sentiment classification.

Features

• Retains crucial negations (not, won't, wouldn't, shouldn't, etc.)
• Keeps intensity modifiers (very, most, more, etc.) for better sentiment retention
• Removes only words that do not impact sentiment analysis

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Installation

Install via pip

pip install revised-stopwords

Import and Use in Your NLP Pipeline

from revised_stopwords import get_revised_stopwords

# Get the optimized stopwords list
stopwords_list = get_revised_stopwords()

print(stopwords_list)  # Output: A set of refined stopwords

Example: Removing Stopwords from Text

import nltk
nltk.download('punkt')  # Ensure tokenization is available
from nltk.tokenize import word_tokenize

text = "I don't think this is a very good idea, but it's not the worst."
tokens = word_tokenize(text)

filtered_tokens = [word for word in tokens if word.lower() not in get_revised_stopwords()]
print(filtered_tokens)  # Output retains sentiment words!

Troubleshooting

LookupError: Resource stopwords not found?

Please use the NLTK Downloader to obtain the resource. Run this command once to manually download stopwords

import nltk
nltk.download('stopwords')

ModuleNotFoundError: No module named 'nltk'?

This error means that the nltk library is not installed in your environment.
Ensure NLTK is installed:

pip install nltk

Contributing

Want to improve this package? Feel free to fork the repo, submit PRs, or suggest enhancements!

How to Contribute:

1. Fork this repository to your GitHub account.

2. Clone your forked repo:

   git clone https://github.com/priyaa279/revised_stopwords.git
   

3. Create a new branch for your changes:

   git checkout -b feature-branch-name
   

4. Make your changes and commit them:

   git commit -m "Describe your change"
   

5. Push your branch to GitHub:

   git push origin feature-branch-name
   

Submit a Pull Request (PR) for review. For major changes, please open an issue first to discuss what you'd like to modify.

License

This project is open-source and licensed under the MIT License.