Competitive video gaming is experiencing exponential growth. Advances in technology and global Internet penetration has created highly dedicated fan bases for games played at a competitive level. Game developing companies are beginning to focus their attention on making games for the new eSports market. How avid eSports fans view competitive gaming is disrupting traditional consumption models. Twitch.TV a site that streams live gaming content is seeing massive growth. Now, more than ever, dedicated gamers can live off of playing games – whether by competing in tournaments as sponsored players or running ads on their Twitch.TV live stream while they play. The communities that have developed around different genres of competitive games are as varied as traditional sports such as Major League Baseball or the National Football League. A new industry with a complex infrastructure is developing in this new market. / text

Submitted by Emanuel Varela Cardoso (emanuel.varela@ufcg.edu.br) on 2018-08-31T19:40:20Z No. of bitstreams: 1 FERNANDO FELIX DO NASCIMENTO JUNIOR – DISSERTAÇÃO (PPGCC).pdf: 3433404 bytes, checksum: b5c42ff5d239a6628e636523baabae45 (MD5) / Made available in DSpace on 2018-08-31T19:40:20Z (GMT). No. of bitstreams: 1 FERNANDO FELIX DO NASCIMENTO JUNIOR – DISSERTAÇÃO (PPGCC).pdf: 3433404 bytes, checksum: b5c42ff5d239a6628e636523baabae45 (MD5) Previous issue date: 2017-12-15 / Capes / Apesar da crescente popularidade dos esportes eletrônicos (eSports), ainda há uma escassez de trabalhos acadêmicos que exploram o comportamento de jogo das equipes. Compreender as características que ajudam discriminar entre equipes bem-sucedidas e malsucedidas poderia ajudar as equipes a melhorar suas estratégias, como determinar métricas de desempenho a serem alcançadas. Nesta dissertação, identificamos e caracterizamos padrões de comportamento de equipes com base nos dados de histórico de partidas de League of Legends, um eSport muito popular. Ao aplicar métodos de mineração de dados, como aprendizado da máquina e análise estatística, agrupamos o desempenho das equipes e investigamos para cada grupo como e em que medida essas características influenciam o sucesso e fracasso das equipes. Alguns grupos são mais propensos a terem equipes mais vencedoras do que outros, os resultados do nosso estudo ajudaram a descobrir as características que estão associadas a essa propensão e permitiram modelar métricas de desempenho de perfis de equipe bem sucedidas e malsucedidas. Encontramos ao todo 7 perfis, que foram categorizados em quatro grandes níveis em termos de proporção de equipes vencedoras: Fraco, Mais ou Menos, Bom e Top. / Despite the increasing popularity of electronic sports (eSports), there is still a scarcity of academic works exploring the playing behavior of teams. Understanding the features that help to discriminate between successful and unsuccessful teams would help teams improving their strategies, such as determine performance metrics to reach. In this dissertation, we identify and characterize team behavior patterns based on historical matches data from League of Legends, a very popular eSport. By applying methods from data mining, such as machine learning and statistical analysis, we clustered teams’ performance and investigate for each cluster how and to what extent these features have an influence on teams’ success and failure. Some clusters are more likely to have winning teams than others, the results of our study helped to discover the characteristics that are associated with this predisposition and allowed us to define performance metrics of successful and unsuccessful team profiles. At all, we found 7 profiles in which were categorized into four big levels in terms of winning team proportion: Weak, So-So, Good and Top.

In an attempt to shed light on the further sophistication of opinion leadership in online communities, this study examined the forces and structures that affect their formation in the League of Legends subreddit. By investigating what users thought about the various types of individuals with which the communicate, the researcher hoped to begin to understand and record how those forces work bother on this particular subreddit and in mass media beyond. Opinion leadership continues to be an integral force in deciding what information is consumed by a public and under what frames and agendas it is contextualized. If researchers can operationalize formal definitions for the influences and structures that occur online, they can better navigate the deep waters that are global communication on the internet.

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The work deals with the relationship between game mechanics and user experience. Identifies the basic gameplay mechanics and elements that have the most important influence on the quality of user experience. Research is realized on the example of a specific game using the concept of game design patterns. Part of the work deals with the introduction of this concept. Furthermore, the work deals with the general theories of games, models of classification and history of computer games. Part of the work is a description of the author's practical experience in creating games as a school project.