A Library for webscraping social media platforms (twitter) and using sentiment analysis on them!
Project description
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:
# 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!
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for Social-Media-Sentiment-Analysis-0.1.1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8de2d4f87148c55d10ae511c4718c1f86019371da9d2ca994c76e4adb03a531a |
|
MD5 | 6bae3e526a3af5b45cb65275937354cf |
|
BLAKE2b-256 | b64eb174c53e6e2511d77fbd22e3913dd053c1fb2886fa4d9706cd04e45f773e |
Close
Hashes for Social_Media_Sentiment_Analysis-0.1.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 50b1e214b681dce6a7e9ea42ec2cbbb9f265d92a0506c99d0f8e761e82e546cc |
|
MD5 | 16de345f77e71f5b2e1560bdc1d93c97 |
|
BLAKE2b-256 | 1919a38b644d575f2c8ab1f393f0815ad884ba11dcc7118c7e01292a095ab3ef |