Metadata-Version: 2.1
Name: Social-Media-Sentiment-Analysis
Version: 0.1.0
Summary: A Library for webscraping social media platforms (twitter) and using sentiment analysis on them!
Home-page: https://social_media_sentiment_analysis.readthedocs.io/
Author: Raf Muz
Author-email: CyberRaf01@gmail.com
License: GPLv3
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE

# Social Media Sentiment Analysis

A Library for webscraping social media platforms (twitter) and using sentiment analysis on them!



## Installation

```

pip install social_media_sentiment_analysis

```



## Get started

Get Tweets from twitter and apply sentiment analysis on it:



```Python

# Import Library's

import pandas

from Social_Media_Sentiment_Analysis import Social_Media

from Social_Media_Sentiment_Analysis import NLP_Classification as Classify



tweets = Social_Media.get_tweets ('BTC', 'lang:"en"', 128)  # Get Tweets

tweets, twitter_score = Classify.twitter_indicator (tweets) # Apply Sentiment Analysis



Social_Media.save_tweets( tweets, '', 'tweets', '.csv')     # Save Tweets

tweets = pandas.read_csv ('tweets.csv')                     # Read Tweets



# Print the Results

print (tweets)

print ('\n{0}'.format (twitter_score))

```



And that's the end of the Readme, Thanks for Reading!
