Opinion mining, also known as sentiment analysis, is the technique of extracting the polarity of sentiments such as positive, negative, and neutral from natural languages, particularly English Now a days, people use and express themselves through social media like Facebook, Instagram, Twitter etc. These opinions expressed by people on various events like product advertisements, social issues, elections, etc., can be used in decision making However, going through every comment or viewpoint made on social media is extremely tough. As a result, in this work, we conduct sentiment analysis on Twitter data focused on the 2020 Presidential Election in the United States. Tweets are extracted through twitter API from twitter.com. By using Vader as a model in the Extract Sentiment operator of RapidMiner 9.10, sentiments are extracted as positive, negative, and neutral. In addition, supervised classification techniques such as Decision tree, KNN, and Nave Bayes are used to test the model’s correctness. Among three classification algorithms, Naive Bayes performs well on Twitter data with a performance accuracy of 60.69%.
Skip Nav Destination
Article navigation
11 December 2024
INTERNATIONAL CONFERENCE ON ADVANCED AND APPLIED MATHEMATICAL SCIENCES (ICAAMS2022)
26–27 February 2022
Tiruvannamalai, India
Research Article|
December 11 2024
Sentimental analysis on U. S. election
Dawa Zangmo;
Dawa Zangmo
a)
1
School of Computer Application, Lovely Professional University
, Phagwara, Punjab, India
, 144411
Search for other works by this author on:
Arjumand Iqbal Dar;
Arjumand Iqbal Dar
b)
1
School of Computer Application, Lovely Professional University
, Phagwara, Punjab, India
, 144411
Search for other works by this author on:
Ram Kumar;
Ram Kumar
c)
1
School of Computer Application, Lovely Professional University
, Phagwara, Punjab, India
, 144411
Search for other works by this author on:
Vishnu Narayan Mishra
Vishnu Narayan Mishra
d)
2
Department of Mathematics, Indira Gandhi National Tribal University
, Lalpur, Anuppur, M. P., India
, 484887
Search for other works by this author on:
AIP Conf. Proc. 3005, 020024 (2024)
Citation
Dawa Zangmo, Arjumand Iqbal Dar, Ram Kumar, Vishnu Narayan Mishra; Sentimental analysis on U. S. election. AIP Conf. Proc. 11 December 2024; 3005 (1): 020024. https://doi.org/10.1063/5.0210583
Download citation file:
Pay-Per-View Access
$40.00
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
8
Views
Citing articles via
Inkjet- and flextrail-printing of silicon polymer-based inks for local passivating contacts
Zohreh Kiaee, Andreas Lösel, et al.
Effect of coupling agent type on the self-cleaning and anti-reflective behaviour of advance nanocoating for PV panels application
Taha Tareq Mohammed, Hadia Kadhim Judran, et al.
Design of a 100 MW solar power plant on wetland in Bangladesh
Apu Kowsar, Sumon Chandra Debnath, et al.
Related Content
Sentiment analysis using vader & word cloud techniques
AIP Conf. Proc. (December 2024)
VADER-IT: A sentiment analysis tool for the Italian language
AIP Conf. Proc. (June 2024)
A weighted hybrid recommendation approach for user’s contentment using natural language processing
AIP Conf. Proc. (June 2023)
Cryptocurrency price prediction using the technique of deep learning and sentiment analysis
AIP Conf. Proc. (March 2024)
Customer review sentiment analysis using SVC, KNN and Vader’s sentiment analysis
AIP Conf. Proc. (January 2025)