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YouTube Ad View Sentiment Analysis using Deep Learning and Machine Learning

by Tanvi Mehta, Ganesh Deshmukh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 11
Year of Publication: 2022
Authors: Tanvi Mehta, Ganesh Deshmukh
10.5120/ijca2022922078

Tanvi Mehta, Ganesh Deshmukh . YouTube Ad View Sentiment Analysis using Deep Learning and Machine Learning. International Journal of Computer Applications. 184, 11 ( May 2022), 10-14. DOI=10.5120/ijca2022922078

@article{ 10.5120/ijca2022922078,
author = { Tanvi Mehta, Ganesh Deshmukh },
title = { YouTube Ad View Sentiment Analysis using Deep Learning and Machine Learning },
journal = { International Journal of Computer Applications },
issue_date = { May 2022 },
volume = { 184 },
number = { 11 },
month = { May },
year = { 2022 },
issn = { 0975-8887 },
pages = { 10-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number11/32367-2022922078/ },
doi = { 10.5120/ijca2022922078 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:21:10.304596+05:30
%A Tanvi Mehta
%A Ganesh Deshmukh
%T YouTube Ad View Sentiment Analysis using Deep Learning and Machine Learning
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 11
%P 10-14
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Sentiment Analysis is currently a vital area of research. With the advancement in the use of the internet, the creation of social media, websites, blogs, opinions, ratings, etc. has increased rapidly. People express their feedback and emotions on social media posts in the form of likes, dislikes, comments, etc. The rapid growth in the volume of viewer-generated or user-generated data or content on YouTube has led to an increase in YouTube sentiment analysis. Due to this, analyzing the public reactions has become an essential need for information extraction and data visualization in the technical domain. This research predicts YouTube Ad view sentiments using Deep Learning and Machine Learning algorithms like Linear Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN). Finally, a comparative analysis is done based on experimental results acquired from different models.

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Index Terms

Computer Science
Information Sciences

Keywords

Sentiment analysis Machine Learning Deep Learning Social networks Ad views analysis Support Vector Machine (SVM) Artificial Neural Network (ANN)

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