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Brand2c: An Analytical Tool For Brand Sentiment Analysis Based On Twitter Data

Sentiment analysis which can be also known as “emotion artificial intelligence” or “opinion mining”, refers to the process of determining whether a text contains positive, negative, or neutral emotions by assigning the weighted sentiment scores. Social media has now become an essential business solu...

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Main Author: Tan, Jia Hui
Format: Undergraduates Project Papers
Language:English
Published: 2023
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://umpir.ump.edu.my/id/eprint/40552/1/CB19067.pdf
http://umpir.ump.edu.my/id/eprint/40552/
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spelling my.ump.umpir.405522024-02-29T07:38:46Z http://umpir.ump.edu.my/id/eprint/40552/ Brand2c: An Analytical Tool For Brand Sentiment Analysis Based On Twitter Data Tan, Jia Hui QA75 Electronic computers. Computer science Sentiment analysis which can be also known as “emotion artificial intelligence” or “opinion mining”, refers to the process of determining whether a text contains positive, negative, or neutral emotions by assigning the weighted sentiment scores. Social media has now become an essential business solution and a must for digital presence in today’s digitally connected world. Sentiment analysis is important for companies to learn about their customers’ needs and market trends. The main problem for the companies and the public user is lack of platform for company to know their brand reputation, company and public user does not have a platform to observe the overview of the customers’ opinion on the products from the social media, and company could not know how the customers feel about the competitors’ brands. A web-based analytical tool is developed for brand analysis on online social network which is Twitter to calculate the sentiment scores of the tweets. The web-based application consists of summarize data of the analysis, pie chart of the sentiment, graph for tweets per day, word cloud, table of the tweets with sentiment scores, graph for positive sentiment, graph for negative sentiment, graph for neutral sentiment, and report of the sentiment analysis. The selected development methodology that was used to develop the web-based analytical tool is Scrum as it is a flexible methodology. It enables teams to collaborate. To conclude, this project implements VADER to evaluate various linguistic and grammatical variations, in addition to assigning a score to words. By using VADER in this project, VADER’s capabilities range helps to evaluate a customers’ attitude based on the tweet to make predictions about market values. 2023-02 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40552/1/CB19067.pdf Tan, Jia Hui (2023) Brand2c: An Analytical Tool For Brand Sentiment Analysis Based On Twitter Data. Faculty of Computing, Universiti Malaysia Pahang Al-Sultan Abdullah.
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Tan, Jia Hui
Brand2c: An Analytical Tool For Brand Sentiment Analysis Based On Twitter Data
description Sentiment analysis which can be also known as “emotion artificial intelligence” or “opinion mining”, refers to the process of determining whether a text contains positive, negative, or neutral emotions by assigning the weighted sentiment scores. Social media has now become an essential business solution and a must for digital presence in today’s digitally connected world. Sentiment analysis is important for companies to learn about their customers’ needs and market trends. The main problem for the companies and the public user is lack of platform for company to know their brand reputation, company and public user does not have a platform to observe the overview of the customers’ opinion on the products from the social media, and company could not know how the customers feel about the competitors’ brands. A web-based analytical tool is developed for brand analysis on online social network which is Twitter to calculate the sentiment scores of the tweets. The web-based application consists of summarize data of the analysis, pie chart of the sentiment, graph for tweets per day, word cloud, table of the tweets with sentiment scores, graph for positive sentiment, graph for negative sentiment, graph for neutral sentiment, and report of the sentiment analysis. The selected development methodology that was used to develop the web-based analytical tool is Scrum as it is a flexible methodology. It enables teams to collaborate. To conclude, this project implements VADER to evaluate various linguistic and grammatical variations, in addition to assigning a score to words. By using VADER in this project, VADER’s capabilities range helps to evaluate a customers’ attitude based on the tweet to make predictions about market values.
format Undergraduates Project Papers
author Tan, Jia Hui
author_facet Tan, Jia Hui
author_sort Tan, Jia Hui
title Brand2c: An Analytical Tool For Brand Sentiment Analysis Based On Twitter Data
title_short Brand2c: An Analytical Tool For Brand Sentiment Analysis Based On Twitter Data
title_full Brand2c: An Analytical Tool For Brand Sentiment Analysis Based On Twitter Data
title_fullStr Brand2c: An Analytical Tool For Brand Sentiment Analysis Based On Twitter Data
title_full_unstemmed Brand2c: An Analytical Tool For Brand Sentiment Analysis Based On Twitter Data
title_sort brand2c: an analytical tool for brand sentiment analysis based on twitter data
publishDate 2023
url http://umpir.ump.edu.my/id/eprint/40552/1/CB19067.pdf
http://umpir.ump.edu.my/id/eprint/40552/
_version_ 1822924171705843712
score 13.235362

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