A Simple Approach to Twitter Sentiment Analysis in R Programming Language
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Updated
Jul 24, 2019 - R
A Simple Approach to Twitter Sentiment Analysis in R Programming Language
This project uses Lexicon-based approach for sentimental analysis of 1000 recent tweets of 4 countries. A sentiment score for each tweet is computed to ascertain the overall nature of the tweet.
Front-end implementation code for Twitter Sentiment Analysis using R Shiny
A text mining project that analyzes the sentiments of the people behind the tweets of the top 4 most popular EPL Teams using the NRC Emotion Lexicon
A repo of my marketing analytics projects that cover digital attribution models and social media analytics.
Machine learning implemented for twitter sentiment analysis with R.
The project concerns an international e-commerce company* based in the USA who want to discover key insights from their customer database. They want to use some of the most advanced machine learning techniques to study their customers.
An analysis of Sentiments on Election Day in Karnataka State Elections (India) 2018 using R.
Data collection and visualization of #NCA17 tweets
Scripts in R to publical use
a twitterbot that uses sentiment analysis to interact with and affirm certain points of view
Sentiment Analysis on the tweets downloaded from Twitter
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Shiny Dashboard for Twitter Analytics
Sentiment Analysis using @RealDonaldTrump tweets using RStduio and Tableau
This project was made in R just to know the actual reason behind knowing why people are using python over R. We have implemented naive bayes algorithm in R programming. Give a ⭐ if this project have helped you.
Depression in Kenya is on the rise. This repo is a first step to using data to find ways to address the situation.
A Shiny web application that uses tweets for sentiment and frequency analysis.
Real time web application for collecting up-to-date news from CNN and Twitter
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