1 |
Kim, M. J. and Lee, S. J., 2014, Measures of abnormal user activities in online comments based on cosine similarity, Vol. 24, No. 2, pp. 335-343.
DOI
|
2 |
Kwon, H. Y., 2016, A study on the risk analysis & applicability of SNS data for detecting signs of disaster, Master's theses, Ewha Womans University, pp. 58-60.
|
3 |
Lee, S. H., 2016, Complex disasters and social conflict in south korea: the "Sacrificial System" and process of social cleavage, Discourse 201, Vol. 19 No. 2, pp. 37-61.
DOI
|
4 |
Lim, D. H., 2016, Big data analysis with R, Free academy, Korea, pp. 103-217.
|
5 |
Lim, S. Y., Lim, Y. M. and Lee, J. Y., 2014, Study on the trends of U-City and smart city researches using text mining technology, Journal of the Korean Society for Geospatial Information System, Vol. 22, No. 3, pp. 87-88.
DOI
|
6 |
Park, D. B., 2016, An analysis frame of MERS disease using text and photo images in instagram, Master's thesis, Sungkyounkwan University, pp. 68-74.
|
7 |
Seo, T. W., 2012, A Study of Real-time Disaster Information Extraction and Displayusing the Mash-up based on SNS : using the Twitter API and Google map API, Master's thesis, Pukyong National University, pp. 69-72.
|
8 |
Turney, P. D., 2002, Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews, Proc. of the 40th Annual Meeting of the Association for Computational Linguistics, ACL, Philadelphia, USA, pp. 417-424.
|
9 |
Yoo, C. H. and Hong, S. H., 2015, R visualization, Kyobobook, Korea, p. 672.
|