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, dissertation, 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.


Ira Iryani , Ira Iryani (2013) SENTIMENT ANALYSIS ON PRODUCT TWEETS. Universiti Teknologi Petronas.

Download (553Kb) | Preview


With the advancement of Web 2.0, the user could do more than just retrieve information from a static website. Better user-interface, software and storage facilities all in one place which is called the web browser. One of the main features of this Web 2.0 includes the social media. The hype of social media such as Twitter and Facebook have made people express their opinions and feelings more easily publicly. Everyone interprets the information they got differently. They have their own understanding and interpretation on how the information is. With the technology that is rapidly growing, we can use the information that the user is displaying on social media and make this as opportunity thus identifying the problems as soon as it occurs. Sentiment analysis is about finding subjective information and grouped it into polarity classification (positive, negative or neutral). One of the objectives of this project is, to automatically categorize data into either positive sentiment, negative sentiment or neutral sentiment based on the subjective data that is obtained from the social media. This system can be useful for companies who are interested to get the fastest way to obtain juicy and latest information from the social network. Another target user could be the institutions that are reputation conscious. Case-Base Reasoning (CBR) will be used in this project. CBR is done by looking at past situations to solve the possible same current issue. Large amount of data is hard to comprehend thus, machine learning techniques could be used to automate the tasks and also provide the predictions over that matter.

Item Type: Final Year Project
Academic Subject : Academic Department - Information Communication Technology
Divisions: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Users 2053 not found.
Date Deposited: 28 Feb 2014 11:48
Last Modified: 25 Jan 2017 09:38
URI: http://utpedia.utp.edu.my/id/eprint/13548

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...