• Journal of Korea Game Society
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• v.7 no.4
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• pp.23-31
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• 2007

The study is to explore the ways to design game characters according to the tendency of game users by classifying game users and analyzing the relation between user classes and their preferences towards game characters. The study examines various user classifications based on users' engagement levels, and designs a user questionnaire from them. Based on the result of questionnaire analysis, the study redefines user classes and applies the formal elements of character design to draw on the relationships between user classes and their preferences.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.401-406
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• 2019

Recently, as multi-platform game environments become common, many games of convergence genre have been produced, and the boundaries of genre division by existing platforms have become blurred. The game genre is convergence content consisting of user-centered 'narrative and play'. In this paper, we propose a game genre classification according to the user 's behavior type based on the essential recognition that the subject of the game is the user. The user's actions are done in different genres and goals and rules, and the interaction is an important act for immersion. Therefore, the user's behavioral classification and perception by the game genre are important and expected to help redefine the game structure.

• Journal of Korea Multimedia Society
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• v.25 no.5
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• pp.703-720
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• 2022

Based on the love styles theory used in psychology, this paper classifies users(Passionate Love, Game-playing Love, Friendship Love, Practical Love, Possessive Love, Altruistic Love) and investigates satisfaction with the motivation for using TikTok love videos(Entertainment, Social Relationship, Love skills-learning, Self-verification, Problem-solving) according to the theory of use and satisfaction. First, 414 users were selected to conduct TikTok surveys to collect data. Then, through the analysis of the research results, among the six love types, game-playing type and possessive type have a positive (+) impact on entertainment motivation and love skill-learning motivation. Game-playing type also have a positive (+) impact on social relationship motivation and self-verification motivation. In addition, altruistic type and possessive type are also factors to strengthen the motivation of self-verification. The altruistic type, possessive type and practical type will improve the problem-solving motivation. Finally, through hierarchial multiple regression analysis, it is confirmed that game-playing love type, entertainment motivation, love skill-learning motivation and self-verification motivation can improve user satisfaction. The above results enrich the research of user classification as well as providing inspiration for improving the quality and communication efficiency of TikTok's video and enhancing user experience.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.439-447
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• 2016

Interest in Augmented Reality (AR) game $Pok{\acute{e}}mon$ GO is getting heightened. However, based on its characteristic, various direct and indirect problems are highlighted, thus increasing concerns. Although the game is not formally released domestically, there are limits in national game classification to apply on such outdoor Augmented Reality game. This paper will examine the problematic cases regarding Pokemon GO and analyze internal and external game classification system to discuss safe gaming measures for domestic users. In result of examining cases, need for adding 'physical danger' in current game classification system for user's safety was shown. As the government's game regulation is being eased, appearance of a variety of games using Augmented Reality technology in near future is predicable. Therefore it is important to prepare improvement of game classification system as a pre-safety measure, and it is expected to bring positive effect on game usage and industrial growth through safe game usage.

• Journal of Korea Game Society
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• v.10 no.5
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• pp.65-73
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• 2010

In this paper, we developed the device for an interactive game interface using bio signals which were able to recognize user's motion intention using EMG signals and it was applied to the games which need the information of the muscle motion directions. The module for acquiring EMG signals consists of 4-Ch, wrist-motions were defined as up, right, down and left state. The user's intent was recognized through thresholding and comparing signals of each channel. The classification result of the motion directions could control the arrow keys on the keyboard of PC and it was applied on the various games. This proposed game device can be expected to induce an effective exercise with an interesting and enjoyment, and it can use both self-developed or commercial games.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.6
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• pp.1318-1324
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• 2012

This paper proposes a novel method for Game character classification based on texture and edge orientation feature. The character dose not move(NPC) and move the character is classified. Classification of property within the character of straight line segments are used to extract features. First, the character inside edge feature extraction and then calculates EEDH, SSPD. The extracted attribute represents the energy of a particular direction. Thus, these properties were used to classify of NPC and Monster. The proposed method, the user can reduce the unnecessary time in the game.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.3
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• pp.627-637
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• 2015

As game item trading becomes more popular with the rapid growth of online game market, the market for trading game items by cash has increased up to KRW 1.6 trillion. Thanks to this active market, it has been easy to turn these items and game money into real money. As a result, some malicious users have often attempted to steal other players' rare and valuable game items by using their account. Therefore, this study proposes a detection model through analysis on these account thieves' behavior in the Massive Multiuser Online Role Playing Game(MMORPG). In case of online game identity theft, the thieves engage in economic activities only with a goal of stealing game items and game money. In this pattern are found particular sequences such as item production, item sales and acquisition of game money. Based on this pattern, this study proposes a detection model. This detection model-based classification revealed 86 percent of accuracy. In addition, trading patterns when online game identity was stolen were analyzed in this study.

• Journal of Korea Multimedia Society
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• v.17 no.11
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• pp.1325-1334
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• 2014

Recently game addiction of young people has become a social issue. Therefore, many studies, mostly surveys, have been conducted to diagnose game addiction. In this paper, we suggest how to distinguish levels of addiction based on EEG. To this end, we first classify four groups by the degrees of addiction to internet games (High-risk group, Vigilance group, Normal group, Good-user group) using CSG (Comprehensive Scale for Assessing Game Behavior) and then measure their Event Related Potential(ERP) in the Go/NoGo Task. Specifically, we measure the signals of P300, N400 and N200 from the channels of the NoGo stimulus and Go stimulus. In addition, we extract distinct features from the discrete wavelet transform of the EEG signal and use these features to distinguish the degrees of addiction to internet games. The experiments in this study show that High-risk and Vigilance group exhibit lower Go-N200 amplitude of Fz channel than Normal and Good-user groups. In Go-P300 and NoGo-P300 of Fz channel, High-risk and Vigilance groups exhibit higher amplitude than Normal and Good-user group. In Go-N400 and NoGo-N400 of Pz channel, High-risk and Vigilance group exhibit lower amplitude than Normal and Good-user group. The test after the learning study of the extracted characteristics of each frequency band from the EEG signal showed 85% classification accuracy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1077-1084
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• 2015

Security issues such as an illegal acquisition of personal information and identity theft happen due to using game bots in online games. Game bots collect items and money unfairly, so in-game contents are rapidly depleted, and honest users feel deprived. It causes a downturn in the game market. In this paper, we defined the growth types by analyzing the growth processes of users with actual game data. We proposed the framework that classify hard-core users and game bots in the growth patterns. We applied the framework in the actual data. As a result, we classified five growth types and detected game bots from hard-core users with 93% precision. Earlier studies show that hard-core users are also detected as a bot. We clearly separated game bots and hard-core users before full growth.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.171-173
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• 2021

국내 게임 시장에서도 점차 멀티 플랫폼인 "스팀"을 통해 선정성이 높은 해외 성인 게임이 출시를 하고 있는 중이며 국내 게임 사용자들도 플레이를 해볼 수 있게 되었다. 하지만 국내에서는 심사기관의 제재로 인해 성인 게임을 플레이하고자 하는 사용자들의 의견과 충돌하고 있다. 따라서 본 연구에서는 해외 게임 심사과정과 현황을 조사하고 사용자 설문조사 결과를 통해 국내 게임 시장이 어떻게 받아들어야 하는지 제시하고자 한다.