Analysis on Big Data by Performance Factors of Creative Education using Semi-structured Data-based Twitter

Abstract

As various forms of big data, which includes but not limited to, large volume texts, voice data and videos, are being accumulated whilst the waves of the information age are accelerating progressively, the number of inter-disciplinary analysis solutions with capabilities to use such information is increasing, and accordingly, the developments, such as the drop of costs required for data storage and various Social Network Services, have brought forth the quantitate and qualitative stretch of the data. The phenomenon makes it possible to achieve the types of data usage which were not available in the past, and thus the potential values and leverage of data are on the rise. Studies that that apply such inter-disciplinary analysis system for the improvement of the educational system to suggest future-oriented education system are being carried out at progressive levels. This study has carried out an analysis on big data with Twitter as its subject and suggested, via the natural language process of data and frequency analysis, the quantitative scale indicative of how various issues and performances relating to creative education in South Korea have been handled.