• Journal of Korean Institute of Industrial Engineers
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• v.42 no.3
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• pp.222-230
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• 2016

As the global game market has been more competitive, it has been important to analyze success factors of game products. In this paper, we applied a Bass Diffusion Model and Clustering Analysis to identify the success factors of games based on data from Steam, an international game platform. By using a diffusion model, we first categorize game products into two groups : successful and unsuccessful games. Then, each group has been analyzed by using clustering analysis based on product features such as genres, price, and minimum system requirements. As a result, success factors of a game have been identified. The result shows that customers in game industry appreciate sophisticated contents. Unlike many other industries, price is not considered as a key success factor in the game industry. Expecially, advanced independent video games (commonly referred to as indie games) with killer contents show competitiveness in the market.

• Journal of Korea Game Society
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• v.19 no.1
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• pp.85-94
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• 2019

This paper aims to improve teaching methods for changing the game-related department and game quality management classes of A university from theoretical to practical classes. The main goal is to design and develop a game play analysis system. The design and development of the game play analysis system enables the company to experience the overall process of game development that meets the requirements of the industry. Designs for systems that can improve understanding of game content by experiencing debugging to testing.

• Journal of the Korean Home Economics Association
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• v.39 no.8
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• pp.67-80
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• 2001

The purpose of this research was to find the relationships between use of computer games, computer game addiction and middle school boy's aggression. The subjects were 511 boys of 2 middle schools in Kwang-ju, Korea. The method was self-reporting questionnaire. For data analysis, frequency distribution, percentage, Cronbach's u coefficient were estimated. ANOVA, Duncan test, Pearson's coefficient, and multiple regression analysis were used. The major findings of the research are as follows ; First, most boys(91.4%) play computer game more than once in a week. And have over 2 years computer game experience. Second, computer game addiction score and aggression score, in general, tend to be below the mean scores. Third, boys who play computer game activities of high frequency, start play computer game at earner age, spent playing longer times of computer game, and like more on-line game were addicted to the computer game more than who don't. And boys who spent playing long times on computer game were more aggressive than who don't. Fourth, the influencies of computer game activities variables on aggression were not found significantly. But the influencies of computer game addiction were found significantly.'Negative sentiment $.$ sociality' was the most influencial variable on aggression. The influncies of 'Distortion of the reality'and 'Lost of self-control' was followed.

• Journal of Korea Game Society
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• v.21 no.6
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• pp.125-134
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• 2021

This study examined the themes and methodologies of 89 game studies published in the fields of media studies, youth studies, and psychology. Youth studies and psychology have mainly covered the theme of game addiction and negative effects. Game research in media studies have covered game use and experience, effects, addiction, regulation, game production, game space, discourse, governmental mechanism, game play as labour, etc. Game research in the fields of youth studies and psychology have mainly relied on surveys and experimental design. Game research in media studies included survey, experimental design, in-depth interviews, participatory observation, data crawling, etc.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.75-84
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• 2019

This study was a cross-sectional descriptive research that investigate the level of addiction and analyzed the impact of computer game addiction from 20 to 30 years old on communication capabilities. The purpose of this study was to investigate the level of game addiction according to general characteristics and to confirm the effect of computer game addiction on communication ability. There were a total of 220 participants in the study. This survey for this study was a self-reporting questionnaire, research tools for this study were developed by Lee (2000) using game addiction and Communication ability developed by Frits et al., (1999). Data analysis was analyzed with frequency analysis, t-test, ANOVA, and Regression using SPSS 18.0. As a result of analysis, the difference between game addiction and communication ability by gender was appeared to be different under statistical significance levels: game addiction (t=-.9.2, p<0.01), subcomponents of communication ability, concentration (t=7.20, p<0.01), understanding (t=6.13, p<0.01), response (t=6.22, p<0.01), memory (t=2.88, p<0.05). The highest level of game addiction was appeared between 28 and 30 years old under statistical significance (p<0.01). Finally computer game addiction affects understanding, a subcomponent of communication capabilities.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.635-648
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• 2006

As the advances of Internet infra structure and the support of console and mobile for network games, the industry of online game has been growing rapidly, and the online game traffic in the Internet has been increasing steadily. For design and simulation of game network, the analysis of online game traffic have to be preceded. Therefore a number of papers have been proposed for the purpose of analyzing the traffic data of network games and providing the models. We make and use GameNet Analyzer as a dedicated tool for game traffic measurement and analysis in this paper. We measure the traffic of FPS Quake 3, RTS Starcraft and MMORPG World of Warcraft (WoW), and analyze the packet size, packet IAT(inter-arrival time), data rate and packet rate according to the number of players and in-game behaviors. We also present the traffic models using measured traffic data. These analysis and models of game traffic can be used for effective network simulation, performance evaluation of game network and the design of online games.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1337-1344
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• 2021

This paper presents an interactive educational game design procedure using the DGBL (Digital Game-based Learning) methodology that will help developers to design a multipurpose educational game. The DGBL consists of five stages, which are Analysis, Design, Development, Quality Assurance, and Implementation & Evaluation. This paper is focusing only on the specific technologies included in the Analysis and Design stages based on the DGBL. The first Analysis stage consists of gathering requirements, determining game ideation and learning objectives, and the second Design stage consists of defining the game architecture and database scheme. In this paper, we have designed a lecturers introduction game for a new student or freshmen as a case study to apply the Analysis and Design stages based on DGBL, as well as showing the prototype result in the form of a storyboard.

• Journal of Korea Entertainment Industry Association
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• v.14 no.5
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• pp.49-57
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• 2020

This paper analyzed maximized the tension not by functional restriction but by psychological response inducement to form the tension of the horror game from the point of space time view. In order that, We arranged three major situations inducing the tension in the horror game and prepared space time analysis base. Pure fiction time of game itself is applied on game time excluding the time creating the cut-scene and the game space is organized with various combination of three space types. This analysis result can help horror game design by discovering the relationship between space time structure and tension forming of the horror game. These analysis results allow us to find guidelines for the time and space design of horror games that can be flexibly linked to game events and contexts by controlling the player's dynamic/static tension and temporary/continuous tension.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.59-66
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• 2022

In this paper, by applying IoT technology to the Ultimate game, which is one of the games using Flyingdisc, the process of the game is traced based on the players and the flyingdisc, and a comprehensive relationship analysis between players is performed on the results of the game. A WiFi module with built-in GPS is attached in the players and flyingdisc. The player's ID, latitude/longitude values received from GPS and time are stored in the database in realtime during the game. Process informations of the game is also stored in the database at the same time using mobile Ultimate game App. Based on this informations after the game is over, we developed a system that can perform comprehensive analysis of the game contents. By using the informations stored in the database, the player-based game process and the flyingdisc-based scoring process are visualized in the virtual playground. Various game result informations for players are graphically analyzed using Python.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.157-163
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• 2022

As the online game market grows, the use of game bots is causing the most serious problem for game services. We propose a harvest coordinate analysis model to detect harvesting bots among game bots of the Massively Multiplayer Online Role-Playing Games(MMORPGs) genre. The proposed model analyzes the player's harvesting behavior using the coordinate data. Game bots can obtain in-game goods and items more easily than normal players and are not affected by realistic restrictions such as sleep time and character manipulation fatigue. As a result, there is a difference in harvesting coordinates between normal players and game bots. We divided the coordinate zones and used these coordinate zone differences to distinguish between game bot players and normal players. We created a dataset with NCSoft's AION log and applied it to a random forest model to detect game bots, and as a result, we derived performance with a recall of 0.72 and a precision of 0.92.