Paper Info
Title
The Role of Text Pre-processing in Sentiment Analysis.
Abstract
It is challenging to understand the latest trends and summarise the state or general opinions about products due to the big diversity and size of social media data, and this creates the need of automated and real time opinion extraction and mining. Mining online opinion is a form of sentiment analysis that is treated as a difficult text classification task. In this paper, we explore the role of text pre-processing in sentiment analysis, and report on experimental results that demonstrate that with appropriate feature selection and representation, sentiment analysis accuracies using support vector machines (SVM) in this area may be significantly improved. The level of accuracy achieved is shown to be comparable to the ones achieved in topic categorisation although sentiment analysis is considered to be a much harder problem in the literature.
Year
DOI
Venue
2013
10.1016/j.procs.2013.05.005
Procedia Computer Science
Keywords
Field
DocType
Sentiment Analysis,Text Pre-processing,Feature Selection,Chi Squared,SVM
Data mining,Text mining,Social media,Feature selection,Computer science,Sentiment analysis,Support vector machine,Artificial intelligence,Opinion extraction,Machine learning
Conference
Volume
ISSN
Citations 
17
1877-0509
53
PageRank 
References 
Authors
1.76
17
3
Name
Order
Citations
PageRank
Emma Haddi1531.76
Xiaohui Liu25042269.99
Yu Shi33208264.97