Skip to content

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.

Notifications You must be signed in to change notification settings

Surya-Murali/Sentiment-Analysis-of-Twitter-Data-by-Lexicon-Approach

Repository files navigation

Sentiment-Analysis-of-Twitter-Data-by-Lexicon-Approach

This project uses Lexicon-based approach for sentimental analysis of 1000 recent tweets of 4 countries - USA, India, China and Syria. The general idea is to calculate a sentiment score for each tweet and thereby find out how positive or negative the tweet is.

The sentiment score for each tweet is calculated as follows:
Score = Number of positive words - Number of negative words

  • If Score > 0, the tweet has an overall 'positive opinion'
  • If Score < 0, the tweet has an overall 'negative opinion'
  • If Score = 0, the tweet is said to have a 'neutral opinion'

In order to count the number of positive and negative words in a tweet, an Opinion Lexicon in English is used. It is provided by Hu & Liu and has Positive and Negative Words list. It is taken from: http://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html

Example:

mytest= c("I love John Cena", "Cute cat!", "That was a bad night", "She loves bad boys")

testsentiment = score.sentiment(mytest, pos, neg)

testsentiment

Output:

text score
1 I love John Cena 1
2 Cute cat! 1
3 That was a bad night -1
4 She loves bad boys 0

Note :

  • The code for Twitter-R connection and analysis can be found here
  • The results are shown in the form of Box Plots, histograms and Word Clouds
  • Twitter allows only 15 scrapes in 15 minutes
  • The Twitter Search API searches against a sampling of recent Tweets published in the past 7 days. So only tweets in the last 7 days can be mined
  • Merry Christmas :P

About

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.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages