Exploring the relationship between video game expertise and fluid intelligence

Hundreds of millions of people play intellectually-demanding video games every day. What does individual performance on these games tell us about cognition? Here, we describe two studies that examine the potential link between intelligence and performance in one of the most popular video games genres in the world (Multiplayer Online Battle Arenas: MOBAs). In the first study, we show that performance in the popular MOBA League of Legends' correlates with fluid intelligence as measured under controlled laboratory conditions. In the second study, we also show that the age profile of performance in the two most widely-played MOBAs (League of Legends and DOTA II) matches that of raw fluid intelligence. We discuss and extend previous videogame literature on intelligence and videogames and suggest that commercial video games can be useful as 'proxy' tests of cognitive performance at a global population level

The Dynamics and Frontiers of Video Game Social Research in Communication Studies-A Scientometrics Analysis Based on CiteSpace and VOSviewer

In this media-rich era, digital entertainment in the form of video games has a major impact on our social interaction and productivity in a borderless social mode. As a result, in order to comprehend the research progress of video game, CiteSpace and VOSviewer were used for scientometrics and knowledge mapping in this study. It displays the state of development, fundamental structure, and frontier areas of video game social communication. The mapping is based on 448 publications collected through Web of Science core database searches. The findings indicate that (1) video game social research has gained increasing attention over the last 23 years, with a curvilinear growth in annual publications, but a core authorship group has yet to materialize, and the United States institutions dominate the number of publications on this topic. (2) Gaming behaviors, gender studies, media effects, and gaming experiences have emerged as the four main hotspots of research in this field under the keyword co-occurrence and clustering analyses. (3) Research in this area has traditionally concentrated on violent, addictive, and other problematic gaming behaviors. The findings of this study forecast future trends in the study of video game social communication and provide the groundwork for more in-depth research

Performance analysis in esports: modelling performance at the 2018 League of Legends World Championship

© The Author(s) 2020. Performance analysis is a well-established discipline in sports science, supported by decades of research. Comparatively, performance analysis in electronic sports (esports) is limited. Therefore, there is an opportunity to accelerate performance outcomes in esports by applying methods grounded in sports science. This study adopted a coach-centred approach to model performance at the 2018 League of Legends World Championship. Three expert coaches rated the proposed relationship between 43 variables and match outcomes in professional League of Legends competition using a Likert scale (1–10). The Likert scale was anchored with ‘no relationship’ at 1 and ‘very strong relationship’ at 10. The coaches’ median ratings were calculated for each variable. Variables with a median score ≥6 were retained for analyses. A total of 14 variables were collected from the 2018 League of Legends World Championship (n = 119) matches via video annotations and match histories. Generalized Linear Mixed Effects Models with binomial logit link function were implemented with respect to the Blue Side winning or losing the match, and individual teams were specified as random effects. Variables were screened for multicollinearity before using a step-up approach. The best model of performance included Tower Percentage (p = 0.006) and Number of Inhibitors (p = 0.029). This model achieved classification accuracy of 95.8%. While Tower Percentage and Number of Inhibitors contributed to winning or losing, further research is required to determine effective strategies to improve these variables, to understand the relevance of these variables across the complete time-series of the match, and to determine whether performance indicators remain stable across game updates

Videogame Correlates of Real Life Traits and Characteristics.

This thesis attempts to link real life cognitive traits and demographics with in-game player created data. The first experiment focuses on the nicknames chosen by players and the information one can extract from them. Players with nicknames with negative valence (highly racist or vulgar) tend to report others more and receive more reports from other players themselves when compared to their peers. Additionally, many individuals tend to have their real birthdate appended to their nickname (“Jim1986”). This is the first study that has successfully shown this phenomenon. Additionally, by using the extracted dates I showed that negative interactions tend to diminish as one ages. In my second experiment I linked age with in-game performance, as indicated by rank for the videogame League of Legends (LoL). More specifically, performance in LoL tends to peak in one’s mid to late twenties while performance in first person shooters tends to follow a different pattern with an earlier peak; both seem to have a drop after 28. Moreover, I showed that fluid intelligence, as measured by the Wechsler Abbreviated Scale of Intelligence, as well as rotational working memory, which is an overlapping construct, are positively correlated with in-game rank suggesting they are the driving force between the age-rank findings. Finally, I examined personality through the HEXACO framework. One of the most consistent findings in personality research is the existence of Neuroticism or Emotionality which is why it was my choice of focus. Individuals scoring highly on Emotionality, which is a trait linked to anxiety and sentimentality, tend to underperform in the competitive ladder. This was replicated with two videogames of different genres: Hearthstone and LoL. This thesis suggests that we can successfully extract meaningful information at a mass level through commercial videogames

What World of Warcraft is Teaching Us About Learning.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Rational Agent Architecture to Recommend which Item to Buy in MOBA Videogames

Los videojuegos multijugador de arena de batalla en línea (MOBA), es un genero de videojuegos que durante la última década han ganado popularidad en la escena competitiva de los E-Sports. Este incremento en su popularidad y la complejidad propia de los mismos han llamado la atención de investigadores en todas las áreas del conocimiento, incluyendo la Inteligencia Artificial. Dichos investigadores han utilizado una amplia variedad de técnicas de Aprendizaje de Maquina buscando mejorar la experiencia de diversos usuarios -jugadores novatos, jugadores expertos, espectadores, entre otros- a través de modelos de predicción, sistemas de recomendación y, aunque se han utilizado técnicas de optimización; estas últimas han sido las menos utilizadas en los videojuegos tipo MOBA. Por ello, el presente trabajo de investigación propone la arquitectura de un agente racional capaz de recomendar a un jugador que objeto comprar para aumentar sus probabilidades de ganar una partida, utilizando una técnica de optimización para la generación de recomendaciones. En la arquitectura propuesta, el agente percibe su ambiente con la información disponible en el API del videojuego League of Legends -uno de los MOBA mas populares actualmente-. Tal información es interpretada por una Regresión Logística que durante las etapas tempranas del juego demostró tener una precisión alrededor de 0.975. A su vez, la técnica de optimización seleccionada para generar la sugerencia fue GRASP; en promedio cada sugerencia es generada en 0.36 segundos, estas sugerencias durante la experimentación lograron aumentar la probabilidad de ganar una partida en promedio 5.2x.Multiplayer online battle arena (MOBA) video games are a genre of video games that during the last decade have gained popularity in the competitive E-Sports scene. This increase in popularity and MOBA’s complexity have attracted the attention of researchers in all areas of knowledge, including Artificial Intelligence (AI). AI researchers have used a wide variety of Machine Learning techniques seeking to improve the experience of various users - novice players, expert players, spectators, among others - through prediction models, recommendation systems and optimization algorithms. However, optimization algorithms have been the least used in MOBA videogames. For that reason, this research proposes the architecture of a rational agent capable of recommending to a player what item to buy to increase his probabilities of winning a game, using an optimization technique for generating recommendations. In the proposed architecture, the agent perceives his environment with the information available in the API of League of Legends -currently, one of the most popular MOBA videogames -. Such information is interpreted by a Logistic Regression that during the early stages of the game was shown to have an accuracy around 0.975. Additionally, the optimization technique selected to generate the suggestion was GRASP. On average each suggestion is generated in 0.36 seconds. During experimentation, these suggestions increase the probability of winning a game on average 5.2x.Magíster en Inteligencia ArtificialMaestrí

Spontaneous Communities of Learning: Cooperative Learning Ecosystems Surrounding Virtual Worlds

This thesis is the culmination of a five year research project exploring online gamers and the cultures they engage with, both virtually in the many massively multiplayer games and virtual worlds online, and in the physical spaces they inhabit in various play spaces around the world. The primary research questions concerned social learning in such spaces, i.e. how do players learn from one another what they need to be successful, and what are the associated norms and practices for doing so? What sorts of peripheral skills are gained, and are they applicable to physical world contexts? Finally, what does participation in such spaces mean for individuals who may have lacked other mechanisms for social learning, and what impacts might such findings have on existing educational structures? I anticipate that this thesis will generate as many questions as it will answer, and I hope, that as a snapshot of a gaming culture in time, will be looked upon as a monograph in the classic ethnographic tradition

Gender disparities in esports – An explanatory mixed-methods approach

Within the last decade, esports (i.e., the competitive play of video games) has conquered substantial parts of digital entertainment with annually increasing revenue and consumer participation. Interestingly, while there exists a wide variety of esports titles, there is an observable gender disparity across them, as female esports players are substantially underrepresented at both casual and particularly at professional levels. Building on expectancy theory and achievement motivation, this study used an explanatory follow-up mixed-methods approach to explore the observed gender disparity. Using the exemplary case of League of Legends, we carried out a cross-sectional survey with both male and female League of Legends players. The results were mostly in line with expectancy theory showing no difference regarding expectancy and instrumentality between male and female players. Additionally, contrary to our hypotheses, we found higher valence and achievement motivation levels for female players. We facilitated three online focus-group discussions, each with a different gender distribution (female vs. mixed vs. male), to derive potential explanations for the findings. From the analysis of the focus-group discussions, we demonstrated that cultural and dispositional differences contribute to the observed gender differences. Among these, the differing perceptions of in-game culture and individual attributions (i.e., goal orientation, locus of control) were prevalent reasons influencing female participation.Peer reviewe