International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 180 - Number 34 |
Year of Publication: 2018 |
Authors: Bhumika Pahwa, S. Taruna, Neeti Kasliwal |
10.5120/ijca2018916865 |
Bhumika Pahwa, S. Taruna, Neeti Kasliwal . Sentiment Analysis- Strategy for Text Pre-Processing. International Journal of Computer Applications. 180, 34 ( Apr 2018), 15-18. DOI=10.5120/ijca2018916865
It “is taxing to understand the current trends in the online market and then abridge the general opinions about the products due to the existence of diversified social media data. This has created a need for real time opinion mining which is analysis of the sentiments that classifies the text into positive and negative emotion polarities. In this paper, the author explores the most important step in sentiment analysis that is data pre-processing and analyses the different techniques used for pre-processing in R. The results show that using library packages provides better results with respect to the method where direct functions are used.”