Aspect based sentiment analysis for United States of America Airlines

Joshi, Swapn (2017) Aspect based sentiment analysis for United States of America Airlines. Masters thesis, Dublin, National College of Ireland.

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Abstract

Around the world, internet plays a significant role when it comes to decisions making. Nowadays, a large population of people shares their opinions and views on the internet through social media, blogs and other online platforms. This leads internet to be full of information both relevant and irrelevant. Therefore, in order to get the desired information, it is not possible to go through each document present on the internet. Here, Sentiment analysis acts as a panacea to this problem. This research aims to provide a decision support for the customers for selecting the best fit US-based Airline, by providing an Aspect level sentiment analysis from the other customer's opinions present in micro blogging site Twitter and online review site Skytrax. The proposed research will follow a modified Knowledge discovery and data mining (KDD) methodology. Several machine learning algorithms are applied in order to find out the best-fit algorithm for the system. Also, evaluation is measured based on the performance matrix for the system.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > World Wide Web > Websites > Online social networks T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web > Websites > Online social networks
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Caoimhe Ní Mhaicín
Date Deposited:	28 Aug 2018 08:38
Last Modified:	28 Aug 2018 08:38
URI:	https://norma.ncirl.ie/id/eprint/3077

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