Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 12, Issue 2


Published
on

April 5, 2021


Pages

1521-1531


DOI

Article

A Comparative Analysis of Emotion and Sentiment Analysis Method from Twitter Text


Authors

S. Lavanya Affiliation:
Department of Computer Science and Engineering, Muthayammal Engineering College(Autonomous), Rasipuram, Tamilnadu
, T. Kowsalya Affiliation:
Department of Electronics and Communication Engineering, Muthayammal Engineering College(Autonomous), Rasipuram, Tamilnadu
, J. Preetha Affiliation:
Department of Computer Science and Engineering, Muthayammal Engineering College(Autonomous), Rasipuram, Tamilnadu
, V. Sharmila Affiliation:
Department of Computer Science and Engineering, Muthayammal Engineering College (Autonomous), Rasipuram, Tamilnadu
and P. Rupaezhilarasie Affiliation:
Department of Computer Science and Engineering, Muthayammal Engineering College (Autonomous), Rasipuram, Tamilnadu


Abstract

The Study of Sentiment is an area of science that specializes in the analysis of strong emotions expressed in texts. An opinion is a complete perception of a commodity, service, association, individual or some other form of entity about which a given text is conveyed. This work provides valuable knowledge of the roots of sentiment analysis and how sentiment evaluators can be configured. We demonstrated how to construct a basic classifier and use it as an example. These approaches will eventually change and there will still be the need for a more extensive assessment of emotions. Non -textual material has an important significance in analyses. Photos, photographs , animations and other visual material are also useful in performing social research. Of course, I can see that all these hyperlinks provide essential material. Some other ways of using social media are likes, retweets, reviews on posts and much more! It is hoped that common issues such as avoiding irony and sarcasm would be made less ambiguous. However, there will emerge other issues that will have to be tackled.


Keywords

Accuracy, Machine Learning, Natural Language Performance, Processing, Sentiments Ana lysis, Supervised Learning, Twitter


Citation

Lavanya, S., Kowsalya, T., Preetha, J., Sharmila, V., & Rupaezhilarasie, P. (2021). A comparative analysis of emotion and sentiment analysis method from twitter text. Turkish Journal of Computer and Mathematics Education, 12(2), 1521–1531.

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