NAAS Rating: 5.21 new
Journal of Pharmacognosy and Phytochemistry
Vol. 7, Special Issue 1 (2018)
Social media data analysis in sentiment level by using support vector machine
Author(s): Naw Naw and Aye Chan Mon
Abstract: A social media is an intermediary for communication among people. Twitter is one of the most popular social networking services. All types of users can share their thoughts and opinions on various aspects of day to day activities. So social media websites are regarded as rich sources of data for opinion mining. Such data can be well used for sentiment analysis. Sentiment analysis or opinion mining is the computational study of the opinions, attitudes and emotions of the entity. The entity may describe an individual, event or topic. Support Vector Machine (SVM) is able to identify the separated hyperplane which maximize margin the different classes. The system is intended to measure the impact of ASEAN citizens’ social media based on their usage behavior. The system is developed for analyzing National Educational Rate and Crime Rate occurred in Malaysia, Singapore, our country, Myanmar. The system is also aimed to perform social media sentiment analysis by applying machine learning approach of Artificial Intelligence (AI).
How to cite this article:
Naw Naw and Aye Chan Mon. Social media data analysis in sentiment level by using support vector machine. 2018; 7(1S): 609-613.