| Twitter | scarping | snscrape | streamlit | mongodb | customized |

Contains some useful data science snippets in Kaggle notebooks

Twitter scrapping project

Scraping Social networking sites using SNSCRAPE library and uploading it to MongoDB database.

Topic modeling on tweets from users in India over a 2-year period to discover trending topics and discussions

Sentiment analysis and topic modeling of Russia-Ukraine war-related tweets

Modern Language Tool Kit

Twitter Scaping using Snscrape and Streamlit

Sentiment Analysis on Twitter Tweets.

twitter scrape using python

LDA Topic Modelling and VADER Sentiment Analyzer

Project repo for the mapping natural disaster locations from social media project

Twitter Scraping web app created using Streamlit. It scrapes the twitter data for the given hashtag/ keyword for the given period. The tweets are uploaded in MongoDB and can be downloaded as CSV or a JSON file.

Scraping is a technique to get information from Social Network sites. Scraping Twitter can yield many insights into sentiments, opinions and social media trends. Analysing tweets, shares, likes, URLs and interests is a powerful way to derive insight into public conversations.

This Repo scrapes data from some twitter accounts and do some analysis like sentiment analysis on its data. An API is also programmed for Tweets, Replies, Sentiments and Active Audience for each account. Finally, a website is designed to output the data.

Twitter data scraping streamlit app built using snscrape and python.

[ Scrape the Twitter data From the Twitter dependence on given filtration. ] | ( Disclaimer: Twitter blocked the scraping facilities ) | Twitter Scraper | Snscraper | Python | Pandas | Numpy | MongoDB | Pymongo |

This Web application basically scrapes information from Twitter. Users can scrape data by entering any keyword or hashtag.