Welcome To UTPedia

We would like to introduce you, the new knowledge repository product called UTPedia. The UTP Electronic and Digital Intellectual Asset. It stores digitized version of thesis, final year project reports and past year examination questions.

Browse content of UTPedia using Year, Subject, Department and Author and Search for required document using Searching facilities included in UTPedia. UTPedia with full text are accessible for all registered users, whereas only the physical information and metadata can be retrieved by public users. UTPedia collaborating and connecting peoples with university’s intellectual works from anywhere.

Disclaimer - Universiti Teknologi PETRONAS shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.Best viewed using Mozilla Firefox 3 or IE 7 with resolution 1024 x 768.

Social Media Sentiment Analysis - Twitter

MOHAMED SHAHID, AFIQA (2020) Social Media Sentiment Analysis - Twitter. Universiti Teknologi PETRONAS. (Submitted)

[img] PDF
Restricted to Registered users only

Download (3993Kb)


This project gives a method for sentiment analysis specifically aimed to work with Twitter data (tweets), to consider their length, structure and specific language. The method employed makes it able to process tweets in near real time. A large amount of online data, rich web resources are highly unstructured plus such natural language are not resolvable via machine straightforwardly. The increased demand to capture opinions of the public concerning sales of a product has led to study of the field sentiment analysis and opinion mining. Opinion refers to the extraction of lines in raw data which expresses an opinion. Sentiment analysis classifies polarity of extracted sentiments into positive, negative and neutral. This type of analysis commonly applies to analyze the service or product reviews, voice of the purchaser, survey responses from social media feeds and online to analyze the attitude of the client. A dashboard has been created to know the opinion regarding sales of the product whether it has more positive, negative or neutral number. This project will help the product owner to know opinion and thoughts of the social media user about their product.

Item Type: Final Year Project
Academic Subject : Academic Department - Information Communication Technology
Subject: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 06 Sep 2021 09:19
Last Modified: 06 Sep 2021 09:19
URI: http://utpedia.utp.edu.my/id/eprint/20663

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...