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Twitter Sentimental Analysis
Subject area: Science,Engineering and Technology · Area of research: Sentiment Analysis
Abstract
With the growing use of the internet and social media like Twitter, Instagram, WhatsApp, and Snapchat a lot of interaction and data exchange happens. There is rapid growth in the number of users, these users express their thoughts and views which might be personal, and political and people tend to have discussions with different communities. There has been continuous work done in the field of sentimental analysis of Twitter data. This data helps in analyzing the sensitivity factor and in predicting the nature of the user trying to tweet a particular piece of information, thereby avoiding many conflicts and preventing one from posting a controversial piece of information. In this paper, we will discuss the above problem statement.
Keywords
Twitter sentimental analysis, tweets, Natural Language Processing (NLP), Libraries, Naive Bayes algorithm, Support vector machine, Logistic Regression.
References
[1] Natural Language Processing Elizabeth D. Liddy Syracuse University
[2] Twitter Sentiment Analysis by Vedurumudi Priyanka Sridevi Women’s Engineering College, Hyderabad, India (June 13 2021)
[3] NILC-USP at SemEval-2017 Task 4: A Multi-view Ensemble for Twitter Sentiment Analysis Edilson A. Correa Jr., Vanessa Queiroz Marinho, Leandro Borges dos Santos ˆ Institute of Mathematics and Computer Science University of S˜ao Paulo (USP) S˜ao Carlos, S˜ao Paulo, Brazil
[4] How Will Your Tweet Be Received? Predicting the Sentiment Polarity of Tweet Replies Soroosh Tayebi Arasteh∗†‡, Mehrpad Monajem† , Vincent Christlein† , Philipp Heinrich† , Anguelos Nicolaou† , Hamidreza Naderi Boldaji† , Mahshad Lotfinia§ and Stefan Evert† †Friedrich-Alexander-Universitat Erlangen-N ¨ urnberg, Germany ¨ ‡Harvard Medical School, United States §Sharif University of Technology, Iran
[5] Twitter Sentiment Analysis Aliza Sarlan1 , Chayanit Nadam2 , Shuib Basri3 Computer Information Science Universiti Teknologi PETRONAS Perak, Malaysia
[6] Kevin P. Murphy. 2012. Machine Learning: A Probabilistic Perspective. The MIT Press
How to cite this paper
@article{1704484,
author = {Mervyn George, Kavyashree Balaraman, Vinay M, Sapna R},
title = {Twitter Sentimental Analysis},
journal = {Iconic Research And Engineering Journals},
year = {2023},
volume = {6},
number = {11},
pages = {529-535},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1704484.pdf},
abstract = {With the growing use of the internet and social media like Twitter, Instagram, WhatsApp, and Snapchat a lot of interaction and data exchange happens. There is rapid growth in the number of users, these users express their thoughts and views which might be personal, and political and people tend to have discussions with different communities. There has been continuous work done in the field of sentimental analysis of Twitter data. This data helps in analyzing the sensitivity factor and in predicting the nature of the user trying to tweet a particular piece of information, thereby avoiding many conflicts and preventing one from posting a controversial piece of information. In this paper, we will discuss the above problem statement.},
keywords = {Twitter sentimental analysis, tweets, Natural Language Processing (NLP), Libraries, Naive Bayes algorithm, Support vector machine, Logistic Regression.},
month = {May},
}