Volume- 10
Issue- 5
Year- 2022
DOI: 10.55524/ijircst.2022.10.5.7 | DOI URL: https://doi.org/10.55524/ijircst.2022.10.5.7 Crossref
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)
Article Tools: Print the Abstract | Indexing metadata | How to cite item | Email this article | Post a Comment
Milisha , Aman Jatain, Priyanka Makkar
As we all know social media is a growing industry in the current world. People of every age are using social media directly or indirectly. Millions of people are sharing their thoughts on Twitter day by day. Every tweet has its own characteristics and expressions. The technologies I have used for analyzing the datasets of Twitter are data mining and NLP with Python. After collecting the data, we have trained it and made the tweets capable of testing, so it can give us the proper sentimental output. This paper will help us to understand the sentiment analysis techniques and also helps us to extract sentiments from Twitter datasets. The Twitter datasets collected from Kaggle and other sources. In this paper, we have focused on the comparative study of the different algorithms as well as on techniques.
Student, Department of Computer Science & Engineering, Amity School of Engineering and Technology, Gurugram, India
No. of Downloads: 33 | No. of Views: 1027
Dipti Prajapati, Samishtarani Sabat, Sanika Bhilare, Rashmi Vishe, Prof. Suman Bhujbal.
March 2024 - Vol 12, Issue 2
Anu Sharma, Vivek Kumar.
May 2023 - Vol 11, Issue 3
Venkateswaran Radhakrishnan.
May 2023 - Vol 11, Issue 3