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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 9, 2019.
Abstract: The widespread use of Internet has resulted in a massive number of websites, blogs and forums. People can easily discuss with each other about different topics and products, and can leave reviews to help out others. This automatically leads to a necessity of having a system that may automatically extract opinions from those comments or reviews to perform a strong analysis. So, it may help out businesses to know the opinions of people about their products/services so they can make further improvements. Sentiment Analysis or Opinion Mining is the system that intelligently performs classification of sentiments by extracting those opinions or sentiments from the given text (or comments or reviews). This paper presents a thorough research work carried out on tweets’ sentiment analysis. An area-specific analysis is done to determine the polarity of extracted tweets for make an automatic classification that what recent news people have liked or disliked. The research is further extended to perform retweet analysis to describe the re-distribution of reactions on a specific twitter post (or tweet).
Zareen Sharf, Zakia Jalil, Wajiha Amir and Nudrat Siddiqui, “Establishing News Credibility using Sentiment Analysis on Twitter” International Journal of Advanced Computer Science and Applications(IJACSA), 10(9), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100927
@article{Sharf2019,
title = {Establishing News Credibility using Sentiment Analysis on Twitter},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100927},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100927},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {9},
author = {Zareen Sharf and Zakia Jalil and Wajiha Amir and Nudrat Siddiqui}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.