b-ghimire / twitter-sentiment-analysis

R shiny web application to scrape tweets based on user-defined search keyword and perform sentiment analysis of the tweets. Sentiment analysis of tweets consists of classifying tweets into emotion classes (i.e., anger, disgust, fear, joy, sadness and surprise) and also polarity classes (i.e., negative, neutral and positive) using naïve Bayes classifier. The tweets are scraped, classified into sentiment classes and visualized in R using twitteR, sentiment and ggplot2 packages, respectively.

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twitter-sentiment-analysis

R shiny web application to scrape tweets based on user-defined search keyword and perform sentiment analysis of the tweets. Sentiment analysis of tweets consists of classifying tweets into emotion classes (i.e., anger, disgust, fear, joy, sadness and surprise) and also polarity classes (i.e., negative, neutral and positive) using naïve Bayes classifier. The tweets are scraped, classified into sentiment classes and visualized in R using twitteR, sentiment and ggplot2 packages, respectively.


![alt tag](https://raw.githubusercontent.com/b-ghimire/twitter-sentiment-analysis/master/Rapp_twitter/img/plot_polarity.png)
![alt tag](https://raw.githubusercontent.com/b-ghimire/twitter-sentiment-analysis/master/Rapp_twitter/img/plot_emotion.png)

About

R shiny web application to scrape tweets based on user-defined search keyword and perform sentiment analysis of the tweets. Sentiment analysis of tweets consists of classifying tweets into emotion classes (i.e., anger, disgust, fear, joy, sadness and surprise) and also polarity classes (i.e., negative, neutral and positive) using naïve Bayes classifier. The tweets are scraped, classified into sentiment classes and visualized in R using twitteR, sentiment and ggplot2 packages, respectively.


Languages

Language:R 100.0%