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Twitter Data Classification by Machine Learning for Sentiment Analysis

Pragya Mishra; Rajesh kumar Nigam
In this paper is proposed method that performs classification of tweet data sentiment on Twitter. Twitter is an online social networking website that contains a rich amount of sentiment data that can be structured, semi-structured and unstructured data that can help to analyze behavior of guy. Data classification and analyzing is big task. Here is used Naïve Bayes classifier to classify data and used machine learning to analysis human behavior. Tweet analysis is work two basic mode : (A) sentiment expressed by a phrase in the context of a tweet, and (B) overall sentiment of a tweet. It is implemented with the help of python Ecosystem to improve its scalability and efficiency. In this sentiments analysis process also refer the NLP (Natural language processing). It is internal action process between human and computer, it analyzes the treasure of natural language data Here we get idea how to mine twitter data to get sentiment. Here we used deep neural network and text mining algorithm to extract all text data to analysis accurate opinion of all user and increase accuracy.
Select Volume / Issues:
Year:
2021
Type of Publication:
Article
Keywords:
Sentiment Analysis; Natural Language Processing; Twitter Data; Naive Baise Classifier; SVM; Textblob
Journal:
IJECCE
Volume:
12
Number:
2
Pages:
43-50
Month:
March
ISSN:
2249-071X
Hits: 161

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