Earticle

The purpose of this study was to examine the difference of middle school students’ game-oriented life according to their game usage patterns. The subjects of the study was 1,861 school students included in the panel data from the survey conducted by The National Youth Policy Institute. For data analysis, SPSS WIN 21 program was used to conduct one-way ANOVA. The result shows that the frequency of game play, the number of hours they play game on weekdays and weekends and the time span of game play were related to the game-oriented life. However, this tendency was not applied to those who don't play game at all. This suggests it could be more desirable to regulate students to play game for an appropriate amount of time rather than prevent them from playing games at all, when it comes to the matter of the potential problem according to playing games.

In recent years, with the increasing popularity of diverse online social network sites, such as Facebook, Twitter, Blogger, YouTube, LinkedIn, and MySpace, a massive amount of data has become available. Applying data mining techniques to social media can yield interesting perspectives to understanding individual and human behavior, detecting hot issues and topics, or discovering a group and community. This study aims to address the question of how people use Twitter and to assess the power of Twitter in terms of creating consumer interest in commercials based on an analysis of Twitter messages about various Super Bowl ads. Instead of relying on the audience’s responses, this study adopts a hybrid approach, combining a data-mining approach to collect, filter and analyze a massive amount of tweets with manual content analysis.