• Journal of Korea Game Society
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• v.9 no.6
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• pp.3-10
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• 2009

what is the elements letting users play games consistently other than the growth of the computer technology? What sort of elements can games give to control the balances in the various features of users? The subject of this study was set up for these questions. Examining the result of this study, the analysis of the types of individual characteristics as well as their preferences of playing games in the level of game design in the process of game development can be utilized as a fundamental data for the design of game contents based on user's propensity. Also it can provide the most effective method for controlling the balance of the game world. Moreover, it can be utilized to set up directions for updating the games based on user's propensity. If it can be counted for the potential users' preferences, the result of analysis of individual characteristic would act as good basic data for the balancing of game among various types of users.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1191-1199
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• 2010

Knowing what factors into a player's ability to affect the outcome of a sports game is crucial. This knowledge helps determine the relative degree of contribution by each team member as well as sets appropriate annual salaries. This study uses statistical analysis to investigate how much the outcome of a professional baseball game is influenced by the records of individual players. We used the Lotte Giants' data on 252 games played between 2007 and 2008 that included environmental data(home or away games and opponents) as well as pitchers' and batters' data. Using a SAS Enterprise Miner, we performed a logistic regression analysis and decision tree analysis on the data. The results obtained through the two analytic methods are compared and discussed.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.3
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• pp.23-40
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• 2014

This paper measures the operational efficiency of domestic online game companies and analyze its trends and patterns by using data envelopment analysis (DEA). DEA is a non-parametric approach to measuring the relative efficiency of decision-making units (DMUs) with multiple inputs and outputs. 14 online game companies are selected as DMUs and three inputs (number of employees, capital and asset) and three outputs (sales, operating profit and net profit) are selected as DEA variables. First, the output-oriented BCC model and super-efficiency model are employed to measure the static operational efficiency of the online game companies from 2003 to 2012. We also conduct the dynamic analysis with DEA window model to capture the trends of their operational efficiency influenced by internal and external environmental changes. The results are expected to provide fruitful implications for strategic decision making of online game companies and policy making for the online game industry.

• Journal of Korea Game Society
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• v.15 no.3
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• pp.177-188
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• 2015

In-game cheating by the use of unauthorized software programs has always been a big problem that they can damage in First Person Shooting games, although companies operate a variety of client security solutions in order to prevent games from the cheating attempts. This paper proposes a method for detecting cheaters in FPS games by using game log analysis in a server-side. To accomplish this, we did a comparative analysis of characteristics between cheaters and general users focused on commonly loaded logs in the game. We proposed a cheating detection model by using artificial neural network algorithm. In addition, we did the performance evaluation of the proposed model by using the real dataset used in business.

• 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.

• Journal of Korea Game Society
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• v.16 no.2
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• pp.7-16
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• 2016

In this paper, we propose a method for effectively detecting specific behavior. The proposed method detects outlying behavior based on the game players' characteristics. These characteristics are captured non-invasively in a general game environment and add keystroke based on repeated pattern. In this paper, cameras were used to analyze observed data such as facial expressions and player movements. Moreover, multimodal data from the game players was used to analyze high-dimensional game-player data for a detection effect of repeated behaviour pattern. A support vector machine was used to efficiently detect outlying behaviors. We verified the effectiveness of the proposed method using games from several genres. The recall rate of the outlying behavior pre-identified by industry experts was approximately 70%. In addition, Repeated behaviour pattern can be analysed possible. The proposed method can also be used for feedback and quantification about analysis of various interactive content provided in PC environments.

• Journal of Sport and Applied Science
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• v.8 no.3
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• pp.13-19
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• 2024

Purpose: This study aims to investigate the consumption patterns of the MZ generation in relation to eSports and traditional professional sports, focusing on the similarities and differences in spending behavior on game items and professional sports viewing. Research design, data, and methodology: The research utilizes a comparative analysis of eSports and professional sports consumption trends within the MZ generation. Data was collected through surveys targeting MZ generation consumers and analyzed using statistical methods to assess the impact of consumption behaviors on spending. The study particularly focuses on the expenditure behaviors in game items (eSports) versus traditional sports viewing expenses. Results: The analysis revealed that the MZ generation displays distinct consumption behaviors between eSports and traditional sports. eSports consumption is characterized by higher spending on in-game items, driven by personalization and competitive advantages, whereas spending on professional sports viewing is influenced by fan loyalty and event participation. Conclusions: The findings underscore the growing economic significance of eSports, driven by the unique consumption behaviors of the MZ generation. These insights suggest that the eSports industry should continue to adapt its strategies to capitalize on this trend, while traditional sports organizations may need to innovate in engagement strategies to maintain consumer interest and expenditure.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.189-196
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• 2018

Player's actions in a game occur in the process of gameplay experiences in a play space designed by the developer according to preset gameplay beats. Focusing on beats that induce a first-person shooter (FPS) game's main gameplay, this paper analyzes the differences in eye gaze information found in different players during the course of gameplay. For this research goal, the study divides the beat areas in which play actions appear in association with gameplay beats at a typical FPS game level, repeatedly conducts tests in accordance with a player's experience level (novice and expert group), and collects and analyzes eye gaze information data in three types of beat areas. The analysis result suggests concrete guidelines for game level design for different beat areas based on an FPS game player's experience level. This empirical experiment method and result can lessen repetitive modification work for game level design and consequently be utilized for optimizing the game level to the developer's intention.

• Journal of Korea Game Society
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• v.21 no.6
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• pp.13-30
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• 2021

This paper analyzed the user's presence experience and player experience in FPS according to game usage time using Steam's review data. Data was obtained through crawling using Python. In analysis result, it was confirmed that issues related to controllable physical presence and uncontrollable social presence emerged in the group with less game use time, and controllable physical presence was changed to controllable social presence in the group with more play timeFurthermore, through player experience analysis, it was found that the keyword "recoil," a factor in game play, was important.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1626-1635
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• 2016

This study examines whether online game motivation, with social and expedition needs, are associated with the degree of loneliness among young adolescents. Using data from a survey of 2014 elementary-, middle- and high-school students in South Korea, a three-wave online survey was conducted to collect data from online players. Two latent growth cause-and-effect models were developed to test whether online game motivation influences degree of loneliness. Results showed that both social and expedition needs are positively associated with loneliness. This study contributes to the knowledge of the underlying needs for a player with loneliness and also highlights the social and expedition needs as potential therapeutic factors.