Exploring classification for sentiment analysis from halal based tweets
Globally, social media is gaining popularity and redefining how people interact with one another online. Malaysian individuals, for example, are increasingly reliant on social media platforms such as Facebook and Twitter as well as LinkedIn, Pinterest, Instagram, and other similar sites. C...
Saved in:
Main Authors: | , , |
---|---|
Format: | Other |
Language: | English |
Published: |
ResearchGate
2021
|
Subjects: | |
Online Access: | http://eprints.uthm.edu.my/6713/1/P13612_672eb4b3c3f7220482fcda8be619a60a.pdf http://eprints.uthm.edu.my/6713/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Tun Hussein Onn Malaysia |
Language: | English |
id |
my.uthm.eprints.6713 |
---|---|
record_format |
eprints |
spelling |
my.uthm.eprints.67132022-03-14T02:16:27Z http://eprints.uthm.edu.my/6713/ Exploring classification for sentiment analysis from halal based tweets Setik, Roziyani Raja Lope Ahmad, Raja Mohd Tariqi Marjudi, Suziyanti H Social Sciences (General) Globally, social media is gaining popularity and redefining how people interact with one another online. Malaysian individuals, for example, are increasingly reliant on social media platforms such as Facebook and Twitter as well as LinkedIn, Pinterest, Instagram, and other similar sites. Consider sentiment analysis to be a sub-category of social listening. A social media sentiment analysis has uncovered the public's current feelings on a particular topic or brand. Sentiment analysis is a technique for characterizing and capturing emotional states from unstructured text. The most important part of sentiment analysis is to evaluate a body of text to comprehend the opinion expressed by it. It usually assigns a polarity of “positive”, “negative” or “neutral”. It uses an algorithmic technique to capture people's thoughts, sentiments, and emotions by incorporating Natural Language Processing and Machine Learning technology. Sentiment analysis in Malaysia's social media is challenging to perform since posts are frequently written in a mixed language, usage of English and Malay with embedded jargon and various district dialect. The classification was performed based on Malaysia halal certification scheme for each tweet to acquire the class label's frequency value based on the sentiment analysis process's polarity results. It will demonstrate social media users' proclivity for posting and can act as a reference point for users when making decisions. An analysis of amounted 500 tweets with the hashtag #sijilhalal elicited information regarding people's feelings, preconceptions, and attitudes toward various issues related to halal certification in Malaysia. The discovery of a person's emotions concerning halal topics is visualized. Muslims' views are of importance to #sijilhalal awareness. ResearchGate 2021 Other NonPeerReviewed text en http://eprints.uthm.edu.my/6713/1/P13612_672eb4b3c3f7220482fcda8be619a60a.pdf Setik, Roziyani and Raja Lope Ahmad, Raja Mohd Tariqi and Marjudi, Suziyanti (2021) Exploring classification for sentiment analysis from halal based tweets. ResearchGate. |
institution |
Universiti Tun Hussein Onn Malaysia |
building |
UTHM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Tun Hussein Onn Malaysia |
content_source |
UTHM Institutional Repository |
url_provider |
http://eprints.uthm.edu.my/ |
language |
English |
topic |
H Social Sciences (General) |
spellingShingle |
H Social Sciences (General) Setik, Roziyani Raja Lope Ahmad, Raja Mohd Tariqi Marjudi, Suziyanti Exploring classification for sentiment analysis from halal based tweets |
description |
Globally, social media is gaining popularity and
redefining how people interact with one another online.
Malaysian individuals, for example, are increasingly reliant on
social media platforms such as Facebook and Twitter as well as
LinkedIn, Pinterest, Instagram, and other similar sites.
Consider sentiment analysis to be a sub-category of social
listening. A social media sentiment analysis has uncovered the
public's current feelings on a particular topic or brand.
Sentiment analysis is a technique for characterizing and
capturing emotional states from unstructured text. The most
important part of sentiment analysis is to evaluate a body of
text to comprehend the opinion expressed by it. It usually
assigns a polarity of “positive”, “negative” or “neutral”. It uses
an algorithmic technique to capture people's thoughts,
sentiments, and emotions by incorporating Natural Language
Processing and Machine Learning technology. Sentiment
analysis in Malaysia's social media is challenging to perform
since posts are frequently written in a mixed language, usage of
English and Malay with embedded jargon and various district
dialect. The classification was performed based on Malaysia
halal certification scheme for each tweet to acquire the class
label's frequency value based on the sentiment analysis
process's polarity results. It will demonstrate social media
users' proclivity for posting and can act as a reference point for
users when making decisions. An analysis of amounted 500
tweets with the hashtag #sijilhalal elicited information
regarding people's feelings, preconceptions, and attitudes
toward various issues related to halal certification in Malaysia.
The discovery of a person's emotions concerning halal topics is
visualized. Muslims' views are of importance to #sijilhalal
awareness. |
format |
Other |
author |
Setik, Roziyani Raja Lope Ahmad, Raja Mohd Tariqi Marjudi, Suziyanti |
author_facet |
Setik, Roziyani Raja Lope Ahmad, Raja Mohd Tariqi Marjudi, Suziyanti |
author_sort |
Setik, Roziyani |
title |
Exploring classification for sentiment analysis from halal based tweets |
title_short |
Exploring classification for sentiment analysis from halal based tweets |
title_full |
Exploring classification for sentiment analysis from halal based tweets |
title_fullStr |
Exploring classification for sentiment analysis from halal based tweets |
title_full_unstemmed |
Exploring classification for sentiment analysis from halal based tweets |
title_sort |
exploring classification for sentiment analysis from halal based tweets |
publisher |
ResearchGate |
publishDate |
2021 |
url |
http://eprints.uthm.edu.my/6713/1/P13612_672eb4b3c3f7220482fcda8be619a60a.pdf http://eprints.uthm.edu.my/6713/ |
_version_ |
1738581526028746752 |