Sentimental Analysis of Twitter Data Using Tweepy and Textblob - Bhuvaneswari Balachander, Praneeth Sai. J.V (International Journal of Advanced Science and Technology, 2020)
In today’s world majority of the people’s decision is based on the news and comments in the social media. World Wide Web has the bulk amount of information where the users can study the opinion of the other users about the news in social media or tweets in the twitter. This paper concludes the that the reviews of the customers is either positive, negative or it may lie between them. To analyze the opinion of the customer various techniques and Machine learning algorithms are used. Firstly the preprocessed dataset has been extracted.After the extraction of the dataset the adjectives of dataset are extracted.The meaningful adjectives are called function vector, then pick out the feature vector list and follow the machine gaining knowledge of algorithms namely Naïve Bayes, Maximum Entropy, SVM and Semantic orientation. Finally measure the overall performance of classifier in phrases of precision and accuracy.