Proceedings ArticleDOI
Comparative Analysis of Context Based Classification of Twitter
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TLDR
This article has verified the twitter’s automated classification results with manual classification by experts, and compared the classified results with SVM, Linear Regression, Logistic Regression and Naive Bayes implemented in Weka tool.Abstract:
Social media offers online data source where internet users’ share their opinions, views and discuss any news or events that happen around the world. Twitter is a popular social media which effectively takes part in any mega event and is used before, during and after live events. Some tweets become trend based on their popularity. The trending tweets are classified by twitter into categories like: Sports (S), Entertainment (E), Politics (P), and Technology (T) which are used in our work. We have used context based meanings to further improve the trending tweet classification results. In this article, we have verified the twitter’s automated classification results with manual classification by experts. Furthermore, we compared the classification results with SVM, Linear Regression, Logistic Regression and Naive Bayes implemented in Weka tool. We found that twitter’s classifier works with almost 89% accuracy in our dataset. This work would contribute in improving misclassification of data of different categories on social media.read more
Citations
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Predicting Elections: Social Media Data and Techniques
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References
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Proceedings ArticleDOI
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Proceedings Article
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Proceedings ArticleDOI
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