![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltext_open_medium.gif)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltext_restricted_medium.gif)
Emotion Classification of Twitter Data Using Lexicon Based Approach
Subscribe/Renew Journal
The main aim of sentiment analysis is to determine the attitude of a speaker or a writer with respect to some topic. The sentiment classification has been classified into two types which are emotional classification and polarity classification. This research work has been done by using emotional classification, which is used to classify the emotions such as joy, fear, disgust, anger, sad and surprise. These six types of emotions are classified using twitter dataset. The classified emotions are visualized using graph. The work is focused on analyzing the tweets of people for Donald Trump and Hillary Clinton and classifies the sentiment from tweets.
Keywords
Emotion, Sentiment Analysis, Naive Bayesian Algorithm, Lexicon, Word Cloud, Visualization.
User
Subscription
Login to verify subscription
Font Size
Information
![](https://i-scholar.in/public/site/images/abstractview.png)
Abstract Views: 200
![](https://i-scholar.in/public/site/images/pdfview.png)
PDF Views: 1