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SENTIMENT ANALYSIS OF ENGLISH TWEETS USING BIGRAM COLLOCATION

📘 Volume 6 📄 Issue 9 📅 september 2021

👤 Authors

Sumaya Ishrat Moyeen, Md. Sadiqur Rahman Mabud, Zannatun Nayem, Md. Al Mamun 1
1. Lecturer, Department of Mechatronics Engineering, Rajshahi University of Engineering & Technology

📄 Abstract

Community and portal websites like Twitter, Facebook, Tumbler, Instagram, and LinkedIn etc. have significant impact in our day-to-day life. One of the most popular micro-blogging platforms is twitter that can provide a huge amount of data which in future can be used for various applications of opinion mining like predictions, reviews, elections, marketing etc. The users use this platform to share their views, express sentiments on various events of their daily life. Previously, many researchers have worked with twitter sentiment analysis and compared various classifiers and got the accuracy below 82%. In this work for classifying tweets into sentiments, we have used various classifiers such as Naïve Bayes, Support Vector Machine and Maximum Entropy that segregate the positive and negative tweets. Using Bigram Collocation with classifiers, weâ??ve acquired 88.42% accuracy.

🏷️ Keywords

Twitter; Sentiment Classification; Machine Learning; NLTK; Python; Naïve Bayes; Support Vector Machine (SVM); Maximum Entropy

🔗 DOI

View DOI - (https://doi.org/10.36713/epra8524)

📚 How to Cite:

Sumaya Ishrat Moyeen, Md. Sadiqur Rahman Mabud, Zannatun Nayem, Md. Al Mamun , SENTIMENT ANALYSIS OF ENGLISH TWEETS USING BIGRAM COLLOCATION , Volume 6 , Issue 9, september 2021, EPRA International Journal of Research & Development (IJRD) , DOI: https://doi.org/10.36713/epra8524

🔗 PDF URL

https://cdn.eprapublishing.org/article/1133pm_38.EPRA JOURNALS. 8524.pdf

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