Sentiment Analysis using Tweets. The tweets (related to a topic/hashtag) used are no more than 7 days old.
Click here for demo.
Select your nearest mirror from here, download and install the pre-compiled distribution with respect to your OS.
- Create a twitter account, if you don't have one yet.
- Go to Twitter Developer and click on "Apply for a developer account".
- login with your twitter account if prompted.
- Select your Primary reason for using Twitter Developer Tools.
- Verify the Twitter Username details associated to the developer account.
- Fill all the data required about your organization.
- Describe your intended use of the Twitter API.
- Describe how you plan to use the Twitter API.
- Accept the Developer Agreement (After reading, obviously) and verify your email account.
- Your application is under review, and you will receive a notification with the result.
- Go to Twitter Developer Apps, login if prompted.
- Click on "create an app".
- Fill up all the required fields and submit.
- Once verified you will be granted the customer and access keys.
Use any IDE or text editor of your interest.
Download and install the packages listed
- NLP
- syuzhet
- tm
- SnowballC
- stringi
- ROAuth
- base64enc
- tm
- ggplot2
- wordcloud
Use the Consumer API key, Consumer API secret key, Access token and Access token secret obtained from the app created on Twitter Developer for "Twitter Access Authentication".
# Twitter Access Authentication
consumer_key <- 'Customer API key here'
consumer_secret <- 'Customer API secret key here'
access_token <- 'Access token here'
access_secret <- 'Access token secret here'Choose the topic you'd like to analyse.
# Fetch tweets
tweets <- searchTwitter("#topic", n=1000,lang = "en")In the "Fetch tweets" cell, replace "topic" with the topic you chose, "n" or the number of tweets related to the topic to be downloaded is set to a 1000 and "lang" or language is set to "English". Parameters "n" and "lang" are changeable.
Run the cells to view the sentiment graph.