• Title/Summary/Keyword: 레전드

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A Study on the Actual Condition of Abuse in PVP Game (PVP 게임에서 어뷰징 실태에 관한 연구)

  • Kim, Jae-Un;Kim, Hyo-Nam
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2020.07a
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    • pp.649-652
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    • 2020
  • 본 논문에서는 스타크래프트 게임이나 리그 오브 레전드 게임 등의 이용자끼리 실력을 겨루는 PVP 형태의 온라인 게임들에서 일어나는 어뷰징에 대해서 실태를 조사하고 이에 따른 개선 방안을 제시한다. 어뷰징에 관하여 알아보고 어뷰징이 게임과 일상에서 어떻게 작용하는지 설명하고 유저들이 어뷰징으로 인한 피해를 입는 사례를 조사하고 현재 개발사들의 조치 방안 및 유저 커뮤니티의 의견 등을 통해 실태에 대해 내용을 제시한다. 결론으로 조사한 자료를 바탕으로 어떻게 하면 어뷰징을 좀 더 방지할 수 있는지에 대한 개선 방안을 제시하고 게임 운영 차원에서 어떤 방식으로 지원해야 하는지를 제시한다.

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A Study on the Character Fun Factor in the MOBA Game Genre (MOBA 게임 장르에서의 캐릭터 재미 요소에 관한 연구)

  • Hong, Min-Gi;Park, Jong-Beom;Kim, Hyo-Nam
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2020.01a
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    • pp.209-212
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    • 2020
  • 게임에서의 캐릭터는 플레이어와 게임을 연결해주는 중요한 역할을 하며, 더 나아가 게임의 재미를 느끼는 데 필요한 요소 중 하나이다. 본 논문에서는 최근 대표적으로 인기를 끌고 있는 MOBA 장르의 게임인 리그 오브 레전드, 오버워치, 히어로즈 오브 더 스톰, 사이퍼즈 총 4개 게임의 캐릭터와 역할에 대한 재미를 분석하여 공통적인 재미 요소를 정리하고 설문 조사를 통해 유저들의 선호도를 파악하여 앞으로 게임 캐릭터 기획 제작에 대해 도움을 주고자 한다.

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A study on content strategy for long-term exposure of YouTube's 'Trending' (유튜브 '인기급상승' 장기 노출을 위한 콘텐츠 전략에 관한 연구)

  • Lee, Min-Young;Byun, Guk-Do;Choi, Sang-Hyun
    • Journal of the Korea Convergence Society
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    • v.13 no.4
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    • pp.359-372
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    • 2022
  • This study aimed to derive a YouTube content strategy that can be exposed to Trending for a long time by comparing the features of 20 channels in the short/long term using 'YouTube Trending' data in 2021. First, through Pearson's correlation analysis, we found that various factors such as 'the number of title or tag letters' related to long-term exposure, and set this as an index to compare features. As a result, 1)'video title' of about 40-45 letters without excessive special characters, 2)'video length' within 10 minutes, 3)'Video description' is effective when writing 2-3 sentences and adding SNS information or including 3 key tags. Also, it would be more effective if you set key tag pairs such as (먹방, mukbang), (역대급, 레전드) derived through text mining. Through this, the channel will spread globally, bringing various advantages, and will be used as an indicator to evaluate the globality of the channel.

Copying Theory in Translating Games: Based on the Game 'League of Legends' (게임 번역에서의 외래어 사용에 대하여: 게임 '리그 오브 레전드'를 중심으로)

  • Won, Ho-Hyeuk;Gu, Bon-Hyeok;Kim, Hyoung-Youb
    • Journal of Korea Game Society
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    • v.18 no.1
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    • pp.135-148
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    • 2018
  • In this study, we suggest that Copying Theory suggested by Pym could be effective in translating games. Languages used in games are based on English because of the history of games mainly developed in America. When people are playing games, people pursue effective communication. Because of this, they transform translated words into simple forms or original foreign languages to communicate each other for effective communication, The usage of English in game translation and communication support the idea that Copying strategy could be effective in translating games.

Prediction of League of Legends Using the Deep Neural Network (DNN을 활용한 'League of Legends' 승부 예측)

  • No, Si-Jae;Lee, Hye-Min;Cho, So-Eun;Lee, Doh-Youn;Moon, Yoo-Jin
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2021.01a
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    • pp.217-218
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    • 2021
  • 본 논문에서는 다층 퍼셉트론을 활용하여 League of Legends 게임의 승패를 예측하는 Deep Neural Network 프로그램을 설계하는 방법을 제안한다. 연구 방법으로 한국 서버의 챌린저 리그에서 행해진 약 26000 경기 데이터 셋을 분석하여, 경기 도중 15분 데이터 중 드래곤 처치 수, 챔피언 레벨, 정령, 타워 처치 수가 게임 결과에 유의미한 영향을 끼치는 것을 확인하였다. 모델 설계는 softmax 함수보다 sigmoid 함수를 사용했을 때 더 높은 정확도를 얻을 수 있었다. 실제 LOL의 프로 게임 16경기를 예측한 결과 93.75%의 정확도를 도출했다. 게임 평균시간이 34분인 것을 고려하였을 때, 게임 중반 정도에 게임의 승패를 예측할 수 있음이 증명되었다. 본 논문에서 설계한 이 프로그램은 전 세계 E-sports 프로리그의 승패예측과 프로팀의 유용한 훈련지표로 활용 가능하다고 사료된다.

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Design and Application of a Winning Forecast Model of the AOS Genre Game (AOS 장르 게임의 승패 예측 모형의 설계와 활용)

  • Ku, Ji-Min;Yu, Kyeonah
    • KIISE Transactions on Computing Practices
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    • v.23 no.1
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    • pp.37-44
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    • 2017
  • Games of the AOS genre are classified as an e-sport rather than a recreational computer game. The involved statistical analyses such as game playing patterns and the season's characters gain importance due to the expertise-requiring nature of sports. In this study, the strategic analysis of computer games was conducted by using data mining techniques on League of Legend, a representative AOS game. We designed and tested a winning forecast model using winning percentage prediction techniques such as logistic regression analysis, discriminant analysis, and artificial neural networks. The game data analysis results were represented by a probabilistic graph and used in the visualization tool for game play. Experimental results of the winning forecast model showed a high classification rate of 95% on average with potential for use in establishing various strategies for game play with the visualization tool.

A Study on Immersion Degree of Players Depending on Figurative Characteristics of Game Characters (게임 캐릭터의 조형적 특성에 따른 플레이어의 몰입도에 관한 연구)

  • Park, Chan-Ik
    • Journal of Digital Convergence
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    • v.18 no.1
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    • pp.271-276
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    • 2020
  • This study is intended to compare and analyze the figurative characteristics of game characters focusing on the MMO shooting game 'Battle Ground' and the MOVA game 'League of Legends,' which currently have the largest number of users in Korea, in order to assess how much effect the figurative shape of game characters has on the immersion of players. As a result, the shape of characters from MOVA or MMORPG games with storytelling as an important factor was revealed to have a greater effect on the immersion degree of players than that of the characters from fast-paced shooting games. In particular, it was found that in games where the level of each character is raised as items are added, the height of most characters is the same as their own eight or nine heads, which is longer than ordinary people.

Development of game indicators and winning forecasting models with game data (게임 데이터를 이용한 지표 개발과 승패예측모형 설계)

  • Ku, Jimin;Kim, Jaehee
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.2
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    • pp.237-250
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    • 2017
  • A new field of e-sports gains the great popularity in Korea as well as abroad. AOS (aeon of strife) genre games are quickly gaining popularity with gamers from all over the world and the game companies hold game competitions. The e-sports broadcasting teams and webzines use a variety of statistical indicators. In this paper, as an AOS genre game, League of Legends game data is used for statistical analysis using the indicators to predict the outcome. We develop new indicators with the factor analysis to improve existing indicators. Also we consider discriminant function, neural network model, and SVM (support vector machine) for make winning forecasting models. As a result, the new position indicators reflect the nature of the role in the game and winning forecasting models show more than 95 percent accuracy.

Effectiveness of e-Sports Online Training Program for Relieving Youth Game Over-flow: Focusing on 'Online LoL(League of Legends) Game School' (청소년 게임 과몰입 해소를 위한 e-스포츠 온라인 수련활동 프로그램 효과성 연구 : '온라인 롤(League of Legends: LoL) 게임학교'를 중심으로)

  • Choi, Junghye Fran;Bang, Seungho
    • Journal of Korea Game Society
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    • v.21 no.5
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    • pp.133-142
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    • 2021
  • This study investigated the effectiveness of 'League of Legends (LoL) game school', an e-sports online training program for relieving youth game over-flow. The Seoul Metropolitan Office of Education's Student Education Institute ran the program. Through this study, it was found that various activities to learn an e-sports game professionally and to explore career paths regarding game had positive effects on students' affections and intrinsic motivation. This study may contribute to helping youth as generation Z understand a healthy game culture.

Predicting win-loss using game data and deriving the importance of subdivided variables (게임데이터를 이용한 승패예측 및 세분화된 변수 중요도 도출 기법)

  • Oh, Min-Ji;Choi, Eun-Seon;Oui, Som Akhamixay;Cho, Wan-Sup
    • The Journal of Bigdata
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    • v.5 no.2
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    • pp.231-240
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    • 2020
  • With the development in the IT industry and the growth in the game industry, user's game data is recorded in seconds according to various plays and options, and a vast amount of game data can be analyzed based on Bigdata. Combined with business, Bigdata is used to discover new values for profit creation in various fields, but it is utilized in the game industry in insufficient ways. In this study, considering the characteristics of the subdivided lines, we constructed a win-loss prediction model for each line using the game data of League of Legends, and derived the importance of variables. This study can contribute to planning of strategies for general game users to get information about team members in advance and increase the win rate by using the record search sites.