Building SYMLOG profiles with an online collaborative game

2009

Abstract Advanced communication technologies enable strangers to work together on the same tasks or projects in virtual environments. Understanding the formation of task-oriented groups is an important first step to study the dynamics of team collaboration. In this paper, we investigated group combat activities in Sonypsilas EverQuest II game to identify the role of player and group attributes on group formation. We found that group formation is highly influenced by playerspsila common interests on challenging tasks.

Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017

Online games provide a rich recording of interactions that can contribute to our understanding of human behavior. One potential lesson is to understand what motivates people to choose their teammates and how their choices lead to performance. We examine several hypotheses about team formation using a large, longitudinal dataset from a team-based online gaming environment. Specifically, we test how positive familiarity, homophily, and competence determine team formation in Battlefield 4, a popular team-based game in which players choose one of two competing teams to play on. Our dataset covers over two months of in-game interactions between over 380,000 players. We show that familiarity is an important factor in team formation, while homophily is not. Competence affects team formation in more nuanced ways: players with similarly high competence team-up repeatedly, but large variations in competence discourage repeated interactions.

Proceedings of the 2013 conference on Computer Supported Cooperative Work (CSCW), 2013

Team collaboration in multi-player online games provides opportunities for players to interact with each other. Facilitating teams has become one of the main design principles to increase social activities. However, there is no research evidence that collaborating on tasks in game teams can produce the desired relational outcome. This paper examines more than half a million solo and team activities during a week in Dragon Nest, an MMO game. We measure the degree of team engagement using the percentage of time played in teams and the percentage of play with repeated teammates, and we then identify different types of players using this. The results show that solo players and team players are two distinct populations and they are highly predictable based on players' in-game status. Moreover, we find that spending more time in teams does not always lead to more social interactions. The interviews with players are conducted to validate the findings.

2015

Multiplayer online battle arena games provide an excellent opportunity to study team performance. When designing a team, players must negotiate a proficiency-congruency dilemma between selecting roles that best match their experience and roles that best complement the existing roles on the team. We adopt a mixed-methods approach to explore how users negotiate this dilemma. Using data from League of Legends, we define a similarity space to operationalize team design constructs about role proficiency, generality, and congruency. We collect publicly available data from 3.36 million users to test the influence of these constructs on team performance. We also conduct focus groups with novice and elite players to understand how players' team design practices vary with expertise. We find that player proficiency increases team performance more than team congruency. These findings have implications for players, designers, and theorists about how to recommend team designs that jointly pri...

2010

The Human Dynamics research group at the MIT Media Laboratory has demonstrated that wearable technology can be used to characterize face-to-face interactions, measure individual and collective patterns of human behavior, and automatically map out a company's de facto organizational chart . This capability can be an extraordinary resource for studying group behavior, group performance and team formation processes.

2010 IEEE Second International Conference on Social Computing, 2010

In this study, we propose a comprehensive performance management tool for measuring and reporting operational activities of teams. This study uses performance data of game players and teams in EverQuest II, a popular MMORPG developed by Sony Online Entertainment, to build performance prediction models for task performing teams. The prediction models provide a projection of task performing team's future performance based on the past performance patterns of participating players on the team as well as team characteristics. While the existing game system lacks the ability to predict team-level performance, the prediction models proposed in this study are expected to be a useful addition with potential applications in player and team recommendations. First, we present player and team performance metrics that can be generalized to all types of games with the concept of point gain, leveling up, and session or completion time. Second, we show that larger or more advanced teams do not necessarily achieve higher team performance than smaller or less advanced teams. Third, we present novel team performance prediction methods based on the past performance patterns of participating players and team characteristics.

2007

Autonomous characters in virtual environments have the potential to improve the interaction experience of users, specially, their social experience. This effect is driven by the interactions occurring between users and the autonomous characters, that in certain scenarios can be in the context of a group. However, for these group interactions to be successful, it is not enough to assure that the autonomous characters behave in a coherent manner from an individual perspective, but it is also necessary that they exhibit behaviours that are coherent with the group composition, context and structure. Therefore, we have developed a model to support believable group dynamics of autonomous characters, inspired in theories developed in human social psychological sciences. This model defines the knowledge that each individual should build about the others and about the group it belongs, and how this knowledge drives their interactions in the group. The model was integrated in the mind of the autonomous characters that perform a collaborative task, in a computer game, with a human player. The game was used in a study that showed that players' interaction experience was better when interaction with groups that followed our model, namely, regarding trust and social identification with the group. In addition, we found some evidence that players prefer playing in groups that have higher level of conflict.

Computers & Education, 2014

We studied the content of the team mental model with a case study about a successful online game team. This team was formed by high-ranking managers in a large raid guild to conduct a raid in War of Worldcraft. They were interviewed with a set of 5-W questions developed according to the conceptualizations of team mental model . Toward the interview protocol, a content analysis was conducted with two-cycle coding method from exploratory to explanatory and a hierarchical framework from code, category, theme, to theory were generated to describe the team mental model. In the first cycle, 17 codes were extracted from participants' own wording for concepts that were shared by whom controlled various gaming characters. These codes are knowledge convergence about the problem at-hand, actors, events, affects and outcomeswhat the core gamers have experienced through the collaborative gaming process. In the second cycle, coding was guided by learning theories. Six categories, mingled from 17 codes, showed collective knowledge of co-work process, leaders' works, work under supervision, seeking joint fun, relationship oriented, and balance between extrinsic-intrinsic motivations. From 6 categories, two themes were synthesized: the team (1) performed "joint hard work" for (2) seeking "joint hard fun." The first theme comprised declarative and procedural knowledge representations and we consider it to be the commonality between this game team and ordinary work/ learning teams. The second theme was composed of affective and cognitive evaluation components about intrinsic motivation which is in accordance with Self-determination theory (SDT, Deci & Ryan, 2000). In general, "Jointly hard work for hard fun" is the gist content of the team mental model. We found ample evidences that members explicitly recall shared motivational beliefs of team mates and emotional-motivational events in gaming. Based on the results of this study, several implications have been addressed for teachers to enhance students' intrinsic motivation in conducting quality Computer-Supported Collaborative Learning. Future studies are needed to further explore the relationship between the quality of team mental models and team-level performance.

Communications in Computer and Information Science, 2019

We propose a novel method called Quantitative Multimodal Interaction Analysis to understand the meaning of interactions from a set of multimodal observable behavior. We apply this method for the measurement of collaborative problem-solving skills in a dyadic online game specially designed for this purpose. We outline our assumptions and describe the machine learning approach that help us tag multimodal behaviors connecting the theoretical construct with the empirical evidence.