Multiplayer Online Battle Arena Games Research Articles

Effects of Mobile Platform on Female Engagement in MOBA Games

Previous research shows that fewer female players participate in competitive games than male players. However, it has been reported that there are more female than male players in King of Glory (KoG), one of the most popular multiplayer online battle arena (MOBA) games on the mobile platform in China. This study aims to investigate how KoG captures the interest of female players at a higher level than other games. We compared the game design of KoG with League of Legends (LoL), one of the most popular MOBA games on the PC platform. We followed up with a semi-structured interview study with 20 participants about their gameplay experiences on the two different platforms. Our analysis indicates that mobility, sociability, and lower barrier to entry are the main factors that drove female players to participate in KoG.

Predicting likelihood of psychological disorders in PlayerUnknown’s Battlegrounds (PUBG) players from Asian countries using supervised machine learning

Multiplayer Online Battle Arena (MOBA) has become one of the most popular genre of online video games played by gamers worldwide. Previous studies have exhibited that excessive engagement in games can lead to Internet Gaming Disorder (IGD). Internet Gaming Disorder has been associated with psychological disorders like impulsivity, anxiety and Attention Deficit Hyperactivity Disorder (ADHD). In this study, we propose an approach to use the game and player statistics along with self-esteem measure of a PlayerUnknown’s Battlegrounds (PUBG, a MOBA game) player to predict whether he/she suffers from IGD and psychological disorders namely ADHD and Generalized Anxiety Disorder (GAD). We extract the game and player statistics of PUBG players from Asian countries and then run several state of the art supervised machine learning models to predict the occurrence of IGD, ADHD, and GAD. Initial experiments and results show that we are able to predict IGD, ADHD, and GAD with an accuracy of 93.18%, 81.81% and 84.9% respectively. Game statistics of PUBG players show strong positive correlation with IGD and ADHD indicating detrimental effects of MOBA games.

A Further Test of the Impact of Online Gaming on Psychological Wellbeing and the Role of Play Motivations and Problematic Use

The impact of increased online gaming play time on psychological wellbeing was examined focusing on the Multiplayer Online Battle Arena (MOBA) game genre. This relationship was explored with respect to motivators for playing and resilience factors. A cross-sectional, online questionnaire design was employed with participants (N = 165) to examine the relationship between weekly average hours played and psychological wellbeing. Five previously reported motivators for playing were tested as mediating variables. In addition, exploratory analyses were conducted to determine the moderating effects of self-esteem and self-efficacy on ‘escapist’ gaming and psychological wellbeing. Results revealed a significant correlation with higher levels of play time associated with poorer psychological wellbeing. This relationship was partially mediated by ‘escapist’ motivation. Self-esteem was found to moderate the negative impact of ‘escapist’ gaming on psychological wellbeing. Research and the associated clinical implications are discussed.

Improving RTS Game AI by Supervised Policy Learning, Tactical Search, and Deep Reinforcement Learning

Constructing strong AI systems for video games is difficult due to enormous state and action spaces and the lack of good state evaluation functions and high-level action abstractions. In spite of recent research progress in popular video game genres such as Atari 2600 console games and multiplayer online battle arena (MOBA) games, to this day strong human players can still defeat the best AI systems in adversarial video games. In this paper, we propose to use a deep Convolutional Neural Network (CNN) to select among a limited set of abstract action choices in Real-Time Strategy (RTS) games, and to utilize the remaining computation time for game tree search to improve low-level tactics. The CNN is trained by supervised learning on game states labeled by Puppet Search, a strategic search algorithm that uses action abstractions. Replacing Puppet Search by a CNN frees up time that can be used for improving units' tactical behavior while executing the strategic plan. Experiments in the μRTS game show that the combined algorithm results in higher win-rates than either of its two independent components and other state-of-the-art μRTS agents. We then present a case-study that investigates how deep Reinforcement Learning (RL) can be used in modern video games, such as Total War: Warhammer, to improve tactical multi-agent AI modules. We use popular RL algorithms such as Deep-Q Networks (DQN) and Asynchronous AdvantageActor Critic (A3C), basic network architectures and minimal hyper-parameter tuning to learn complex cooperative behaviors that defeat the highest difficulty built-in AI in mediumscale scenarios.

Hierarchical Macro Strategy Model for MOBA Game AI

The next challenge of game AI lies in Real Time Strategy (RTS) games. RTS games provide partially observable gaming environments, where agents interact with one another in an action space much larger than that of GO. Mastering RTS games requires both strong macro strategies and delicate micro level execution. Recently, great progress has been made in micro level execution, while complete solutions for macro strategies are still lacking. In this paper, we propose a novel learning-based Hierarchical Macro Strategy model for mastering MOBA games, a sub-genre of RTS games. Trained by the Hierarchical Macro Strategy model, agents explicitly make macro strategy decisions and further guide their micro level execution. Moreover, each of the agents makes independent strategy decisions, while simultaneously communicating with the allies through leveraging a novel imitated crossagent communication mechanism. We perform comprehensive evaluations on a popular 5v5 Multiplayer Online Battle Arena (MOBA) game. Our 5-AI team achieves a 48% winning rate against human player teams which are ranked top 1% in the player ranking system.

Deep Neural Networks for Optimal Team Composition.

Cooperation is a fundamental social mechanism, whose effects on human performance have been investigated in several environments. Online games are modern-days natural settings in which cooperation strongly affects human behavior. Every day, millions of players connect and play together in team-based games: the patterns of cooperation can either foster or hinder individual skill learning and performance. This work has three goals: (i) identifying teammates' influence on players' performance in the short and long term, (ii) designing a computational framework to recommend teammates to improve players' performance, and (iii) setting to demonstrate that such improvements can be predicted via deep learning. We leverage a large dataset from Dota 2, a popular Multiplayer Online Battle Arena game. We generate a directed co-play network, whose links' weights depict the effect of teammates on players' performance. Specifically, we propose a measure of network influence that captures skill transfer from player to player over time. We then use such framing to design a recommendation system to suggest new teammates based on a modified deep neural autoencoder and we demonstrate its state-of-the-art recommendation performance. We finally provide insights into skill transfer effects: our experimental results demonstrate that such dynamics can be predicted using deep neural networks.

Measuring Female Gaming: Gamer Profile, Predictors, Prevalence, and Characteristics From Psychological and Gender Perspectives.

Research investigating female gaming is relatively scarce, and past research has demonstrated that men are more likely to be problematic gamers. Few studies have focused on female gamers in community samples, and those that have been published have mainly collected qualitative data in Europe. There is case study evidence suggesting clinicians are increasingly treating problem female gamers. The aim of this study is threefold: (i) to establish an international female gamer profile, (ii) to determine predictors associated with perceived internet gaming disorder (IGD), and (iii) to identify those who are potentially at risk of developing gaming addiction and its characteristics by applying a quantitative approach. A cross-sectional online survey was applied through international gaming forums recruiting 625 female gamers, assessing sociodemographics, gaming devices used and play genres, and a set of questionnaires on gaming [e.g., problem online gaming (e.g., the nine-item short-form scale to assess IGD: IGDS9-SF), female stereotypes (e.g., sex role stereotyping scale), and psychological symptoms (e.g., Symptom CheckList-27-plus)]. Female gamers from all continents reported the use of all videogames, especially popular online games using computers and consoles. The proportion of gamers with potential IGD was one per cent. Regression analyses identified several risk factors for increased scores on the IGDS9-SF, namely having achievement and social motivations, embodied presence and identification with the avatar, hostility and social phobia together with negative body image, playing Multiplayer Online Battle Arena games, Massively Multiplayer Online Role-Playing Games, and First-Person-Shooter games. Findings contribute to filling the gap in knowledge on female gaming, to aid in the applicability of problematic gaming measurements in female gamers, especially those who are at risk of problematic gaming. The purpose of this study is to enhance the validity of the current measures to diagnose problem gaming appropriately in both genders.

Does Streaming Esports Affect Players’ Behavior and Performance?

In this work, we analyze what effect streaming gameplay on Twitch has on players’ in-game behavior and performance. We hypothesized that streaming can act as a form of implicit incentive to boost players’ performance and engagement. To test this hypothesis, we continuously collected data about all Twitch streams related to a popular Multiplayer Online Battle Arena (MOBA) game, League of Legends (LoL), and data of all LoL matches played during the same time frame, and cross-mapped the two data sets. We found that, counterintuitively, streaming significantly deteriorates players’ in-game performance: This may be due to the burden of carrying out two cognitively intensive activities at the same time, namely, playing the game and producing its commentary for streaming purposes. On the other hand, streaming increases engagement keeping players in significantly longer game sessions. We investigate these two effects further, to characterize how they vary upon individual characteristics.

Internet gaming disorder and psychiatric symptoms in Bengaluru, India: Treatment implication for promotion of user mental health

Background: Psychological distress has been seen among internet users with gaming. There is a need to evaluate the effect of internet gaming on psychological well-being. The present study assessed the depression, anxiety, and stress among users with internet gaming disorder (IGD). Methodology: Sixty users (58 males and 2 females) in the age group of 16–18 years were screened using IGD test for cases with disordered gaming. They were administered background data sheet as well as depression anxiety stress scale. Majority of them were playing multiplayer online battle arena game and first person shooter game. Results: The pattern of use was from 10 to 14 h a day. About 6.8% individuals had lifetime psychiatric history. There was significant positive relationship between the internet gaming and depression (0.412 at 0.05 level), anxiety (0.408 at 0.001 level), and stress (0.308 at 0.05 level) scale. Conclusion: It also implies the need to evolve intensive intervention program to manage internet gaming as well as other psychosocial dysfunctions.

Exploring player experience in ranked League of Legends

ABSTRACTWhile video games provide different Player Experiences (PE), some genres can provide particularly unique PEs driven by their particular features. Such is the case of MOBA (Multiplayer Online Battle Arena) games, currently led in number of players and popularity by League of Legends. In spite of this popularity, PE in MOBA games remains largely unexplored. We aim to explore this gap by presenting a PE study that focuses in League of Legends and its player base. After surveying more than 400 players in the database of the largest eSports organisation in Spain, a series of tests were run from multiple perspectives using the PENS (Player Experience of Need Satisfaction) model and the SPGQ (Social Presence in Gaming Questionnaire) as response variables. Among our findings, we show how PE differs across different levels of competence (or rank) inside the game. When looking at how team play impact PE, results show how PENS dimensions remain unaffected while empathy is driven by playing with known teammates. Role selection, on the other hand, has an arguably insignificant impact in PE. Last but not least, an invariant behavioural engagement across all dimensions shows how players perceive team collaboration as an essential factor for success.

Individual performance in team-based online games.

Complex real-world challenges are often solved through teamwork. Of special interest are ad hoc teams assembled to complete some task. Many popular multiplayer online battle arena (MOBA) video-games adopt this team formation strategy and thus provide a natural environment to study ad hoc teams. Our work examines data from a popular MOBA game, League of Legends, to understand the evolution of individual performance within ad hoc teams. Our analysis of player performance in successive matches of a gaming session demonstrates that a player’s success deteriorates over the course of the session, but this effect is mitigated by the player’s experience. We also find no significant long-term improvement in the individual performance of most players. Modelling the short-term performance dynamics allows us to accurately predict when players choose to continue to play or end the session. Our findings suggest possible directions for individualized incentives aimed at steering the player’s behaviour and improving team performance.

What Makes a Champion: The Behavioral and Neural Correlates of Expertise in Multiplayer Online Battle Arena Games

ABSTRACTDespite the popularity of multiplayer online battle arena (MOBA) games, academic research on MOBA is still very limited. The current study aimed to fill this gap by exploring the behavioral and neural correlates of expertise for the most popular MOBA game, League of Legends (LOL). Three groups of LOL players with different expertise levels were recruited, including professional players, background-matched trainees, and age-matched students with no systematic LOL trainings. A series of behavioral tests and questionnaires was used to evaluate their general cognitive skills and their LOL-specific abilities were extracted from the neural activities (Electroencephalographs (EEG)s and Electrocardiographs (ECG)s) recorded during LOL matches. Using the behavioral features, both the students and the trainees could be significantly separated from the professional players (trainees vs. professional players, 61.11%; students vs. professional players, 66.67%), whereas the students and the trainees cannot be distinguished. Using the neural features, all three groups could be well separated with higher classification accuracies (students vs. trainees: 88.24%; trainees vs. professional players, 93.33%; students vs. professional players, 93.75%). The most contributing behavioral and neural indices were revealed as well, including multiple-object tracking capability, mental concentration, visuospatial attention ability, etc. The authors’ results for the first time showed the possibility of recognizing MOBA expertise using both behavioral and neural measurements and provided a framework for evaluation, selection, and training of professional MOBA players.

MOBA games: A literature review

This article aims to perform a literature review of the available research that focuses strictly on MOBA (multiplayer online battle arena) games. First, a review identifying the relevant papers published since 2011 is conducted, exploring them systematically to extract similarities, gaps and main findings. Results show how League of Legends is the most explored game, with player experience and toxic behaviour as popular topics for research. Second, as MOBA games remain underexplored by researchers despite their vast, enthusiast community, as well as projection and influence on contemporary game designers, a proposal on future lines for research is provided.

Relating conversational topics and toxic behavior effects in a MOBA game

Multiplayer Online Battle Arena (MOBA) games are very competitive and victory relies on effective teamwork. Toxic behavior is a common concern, as it corrodes team effort and harms game ambiance. Related work has focused on the automatic detection of toxic behavior, mostly based on features from the communication channels used by players. In this paper, we investigate the conversational patterns used by players of a popular MOBA game, League of Legends, and their effects on performance and contamination. We identify the main conversation topics exchanged by players using in-game chats; characterize the behavior of each type of player according to these topics; and develop an in-depth analysis of how they affect game performance and toxic contamination. Our findings show that some topics are directly related to toxic behavior. The allies of a toxic player are in general more affected by toxic behavior than the opponents, and in some cases, they act together as a source of toxic behavior. Opponents are more affected when the toxic behavior is directly targeted at them (e.g. racist slurs). Players with no significant contact with toxic players tend to be more positive, concentrating on game tactics and socialization.

Immersive element analysis of the multiplayer online battle arena game genre

The game industry is the total entertainment industry, which includes its entertainingness and popularity and the future planning industry, which allows to create added value with its neighbouring industry. The main purpose of these games development is improving its competitiveness by making satisfied product for users. To make competitiveness game product, it is needed to classify the interested elements and analyse flow elements correctly. In this study, we deducted the content elements from the multiplayer online battle arena (MOBA) game genre and quantified the importance of subdivided elements of focus group interview and semi-Delphi. Play theory-based MOBA's flow elements is analysed by the quantified value of subdivided elements. By this, we propose the developmental direction about interested elements of the MOBA game genre. This study results can be used for contents satisfaction of MOBA game genre and flow evaluation system.

Immersive element analysis of the multiplayer online battle arena game genre

The game industry is the total entertainment industry, which includes its entertainingness and popularity and the future planning industry, which allows to create added value with its neighbouring industry. The main purpose of these games development is improving its competitiveness by making satisfied product for users. To make competitiveness game product, it is needed to classify the interested elements and analyse flow elements correctly. In this study, we deducted the content elements from the multiplayer online battle arena (MOBA) game genre and quantified the importance of subdivided elements of focus group interview and semi-Delphi. Play theory-based MOBA's flow elements is analysed by the quantified value of subdivided elements. By this, we propose the developmental direction about interested elements of the MOBA game genre. This study results can be used for contents satisfaction of MOBA game genre and flow evaluation system.

Russophobia in DotA 2

Online gaming has been a fascinating field of study for the last ten years, especially in the field of socialization (Kolo & Baur, 2004) or even language use and language learning (Thorne, Black & Sykes, 2009). It has become clear that gamers are able to perform processes of identification in completely new ways in these particular contexts, yet forums linked to specific games become a new source of metapragmatic or metadiscursive utterances. Through their experiences in the game, users make comments, assumptions and draw conclusions in order to ‘do identity’ and separate themselves from Others. The aim of this paper will be to analyse the discourses produced in a corpus of forum discussions linked to “DotA 2”, a popular MOBA (multiplayer online battle arena) game where players from every country of the world gather, which leads to specific forms of discrimination—especially towards Russian gamers. In order to analyse these discursive productions and their semantic and pragmatic impacts, we will use three different approaches in order to triangulate our results: a lexicometric analysis (Garric & Capdevielle-Mougnibas, 2009), the semantic study of argumentative possibilities (Galatanu, 2009) and the mobilization of the proximization model (Cap, 2010), in order to understand the semantic variations and dynamics that are at use when gamers publish discourses about Russian players. In particular, we wish to explore how these precise discourses about Russian players are drawing on pragmatics of common sense (Sarfati, 2011), insofar as they rely on prediscourses (Paveau, 2006) to maintain pragmatic effects which imply cognitive impacts on speakers (Maillat & Oswald, 2009) as well as on the interdiscourses at use (Garric & Longhi, 2013).

ANALISIS VISUAL GAME ARENA OF VALOR SEBAGAI DASAR PENGEMBANGAN KONSEP VISUAL GAME

In game design, in addition to having a powerful and interesting gameplay concept, creator should pay attention to the visual aspect embodied in the visual design of the game. Visual aspect is so important to attract user to play it, especially in Multiplayer Online Battle Arena (MOBA) genre game. With the support of visual design, users can easily understand and follow the gameplay faster and and surely they can understand the ability of each character with ease. This research tries to study the visual design and characters design of Arena Of Valor game. With visual perception theory and manga matrix theory to gain an understanding of the visual approach and creator considerations in the game visual design. Hopefully this research can be used as the basis reference for further MOBA game development.

Number processing ability is connected to longitudinal changes in multiplayer online battle arena skill

The popularity of multiplayer online battle arena (MOBA) games provides an opportunity to examine how cognitive skills are linked with changes in player performance within a team-based game genre. There is evidence that video game experience in other genres is connected with specific cognitive skills such as visuospatial attention and working memory capacity. Links have also been observed outside of video games such as numerical intelligence being correlated with the performance of chess experts. In the present study, we investigated whether numerical and working memory ability measured at an initial time-point predicted changes in MOBA skill and gameplay frequency measured five months later. We observed that participants who scored higher on a number processing task had greater improvements in MOBA skill and that this link depended on the social context of the gameplay. Specifically, numerical skill was linked to player rankings generated from matches where they were paired with random individuals; no connection was observed with gameplay that took place with a familiar set of teammates. The results of the present study extend previous research indicating video gameplay is linked to specific cognitive skills, in the case of MOBAs being numerical processing. We suggest that the difference in the connection with number ability to gameplay with novel and familiar players is in line with evidence that the importance of individual performance and the sense of achievement can be reduced in team settings. We suggest that future research should examine what types of quantitative abilities are indicative of MOBA skill and the impact of those factors relative to social skills.

A Visual Analytics Approach for Understanding Reasons behind Snowballing and Comeback in MOBA Games.

To design a successful Multiplayer Online Battle Arena (MOBA) game, the ratio of snowballing and comeback occurrences to all matches played must be maintained at a certain level to ensure its fairness and engagement. Although it is easy to identify these two types of occurrences, game developers often find it difficult to determine their causes and triggers with so many game design choices and game parameters involved. In addition, the huge amounts of MOBA game data are often heterogeneous, multi-dimensional and highly dynamic in terms of space and time, which poses special challenges for analysts. In this paper, we present a visual analytics system to help game designers find key events and game parameters resulting in snowballing or comeback occurrences in MOBA game data. We follow a user-centered design process developing the system with game analysts and testing with real data of a trial version MOBA game from NetEase Inc. We apply novel visualization techniques in conjunction with well-established ones to depict the evolution of players' positions, status and the occurrences of events. Our system can reveal players' strategies and performance throughout a single match and suggest patterns, e.g., specific player' actions and game events, that have led to the final occurrences. We further demonstrate a workflow of leveraging human analyzed patterns to improve the scalability and generality of match data analysis. Finally, we validate the usability of our system by proving the identified patterns are representative in snowballing or comeback matches in a one-month-long MOBA tournament dataset.