Document Type
Conference Item
Publication Date
1-1-2016
Abstract
Sentiment Analysis and opinion mining aims to analyze sentiments, opinions, emotions etc. towards products, services or current topics. There are various approaches applied to mine the sentiments portrayed. Supervised machine learning is one such approach that is generally applied. The aim of this paper is to investigate the current methods used to perform sentiment analysis by reviewing and comparing recently published research. The findings are discussed in hope that it would help future researchers to gain an understanding of a possible method they could adopt or even come up with a new approach to better mine sentiments from big data that is tailored to suit the need of their data source.
Keywords
Sentiment analysis, Naive Bayes, support vector machine, supervised machine learning
Divisions
fsktm
Event Title
International Conference on IT, Mechanical & Communication Engineering (ICIME 2016)
Event Location
Pattaya, Thailand
Event Dates
02-03 January 2016
Event Type
conference