Extraction of tweets and Perform sentiment analysis on the presidential candidature of Donald Trump, Joe Biden and Kanye West in the upcoming elections in US in November, 2020.

Developing a Lambda Architecture pipeline using Apache Kafka, Spark Structured Streaming, Redshift, S3, Python

Twitter Dynamic Dataset Api. Create any dataset YOU want.

Real-time sentiment analysis on tweets using tweepy and kafka. Graphed using the output of a neural network and Dash/Plotly.

Conjunto de utilitários para facilitar a interação do Python com a API do Twitter

Educational bot that posts a tiny flower bed on Twitter every few hours. Check it out if you're new to Python and open source!

Building pipeline to process the real-time data using Spark and Mongodb.

This is a re-tweet bot which retweet with reply for all tweets mentioned with #PyConIndia or #PyConIndia2018 and anyone who mention us @pyconindia .

Tweet After All Commit Messages...have you ever wanted to lose all of your followers by tweeting every single commit message to the world?

Web Mining project in which Descriptive Statistics and NLP techniques are used to analyze the behavior of a Twitter account and the content of their respective tweets.

Twitter Bot: Auto Reply, Like and Retweet according to requirement along with deployment on PythonAnyWhere. (Mainly used for automated customer support reply.)

Automatically updates the twitter banner with the images of 5 latest followers, using tweepy python

A python script which is hosted on cloud to cross post between reddit and twitter using API's with Google sheet integration.

Twitter Spark Streaming using PySpark

Jupyter Notebook with code to help scrape, analyze, organize, and save tweets in CSV files

A Twitter bot that posts a tweet everyday at the same time(8AM EAT) - Built in Python3, tweepy and hosted on PythonAnywhere

The project focuses on minimizing the spread of a rumour in a twitter network by identifying most active or influential users.

A Twitter bot that tweets random Julia sets.

In this project we have built a model which takes a dataset as an input andas an output gives the percentage of posive ,negative and neutral tweets in the given dataset. It is done using natural language processing library using scikit learn machine learning libraries such as textblob.

Identify the counts of hashtags and mentioned accounts and display it as graph and wordcloud