SENTIMENT ANALYSIS ON PRODUCT TWEETS

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.