@article{(Open Science Index):https://publications.waset.org/pdf/10002922,
	  title     = {A Methodology for Investigating Public Opinion Using Multilevel Text Analysis},
	  author    = {William Xiu Shun Wong and  Myungsu Lim and  Yoonjin Hyun and  Chen Liu and  Seongi Choi and  Dasom Kim and  Kee-Young Kwahk and  Namgyu Kim},
	  country	= {},
	  institution	= {},
	  abstract     = {Recently, many users have begun to frequently share
their opinions on diverse issues using various social media. Therefore,
numerous governments have attempted to establish or improve
national policies according to the public opinions captured from
various social media. In this paper, we indicate several limitations of
the traditional approaches to analyze public opinion on science and
technology and provide an alternative methodology to overcome these
limitations. First, we distinguish between the science and technology
analysis phase and the social issue analysis phase to reflect the fact that
public opinion can be formed only when a certain science and
technology is applied to a specific social issue. Next, we successively
apply a start list and a stop list to acquire clarified and interesting
results. Finally, to identify the most appropriate documents that fit
with a given subject, we develop a new logical filter concept that
consists of not only mere keywords but also a logical relationship
among the keywords. This study then analyzes the possibilities for the
practical use of the proposed methodology thorough its application to
discover core issues and public opinions from 1,700,886 documents
comprising SNS, blogs, news, and discussions.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {9},
	  number    = {12},
	  year      = {2015},
	  pages     = {2409 - 2413},
	  ee        = {https://publications.waset.org/pdf/10002922},
	  url   	= {https://publications.waset.org/vol/108},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 108, 2015},
	}