Twitter Sentimental Analysis
Sentiment Analysis is process of collecting and analysing data based upon the person feelings, reviews and thoughts. Sentimental analysis often called as opinion mining as it mines the important feature from people opinions. Sentimental Analysis is done by using various machine learning techniques, statistical models and Natural Language Processing (NLP) for the extraction of feature from a large data.
There are two modules in this projects.
- Trending Hashtags On Twitters &
- Input Strings Or Hashtags.
Twitter Api Twitter Api's must be set. Which can be done by registering to developers site of twitter.For Api to be generated one should request twitter for it in writting.
Requirements For Twitter Sentimental Analysis. Python 3.6 and its versions.
The following are the packages required: Flask Requests NLTK Pickle Statistics Sklearn Wordcloud Matplotlib Sumy Textblob Pandas Os Bokeh Interactor Tweepy
Steps To Be Followed Trending Hashtags On Twitters
Put your Twitter Api in Twitter_Credential.py file. Through Command Promt run the screen_generator.py file. It will start executing. After Executing Successfully, result will be displayed on WEB_OUTPUT.html file.
Inputs String Or Hashtag
Put your Twitter Api in Tweetment.py file. Through Command Promt run the Tweetment.py file. It will give a ip address. Go to that ip address through browser..
ENJOY THE PROJECT....