Visualizing event sequence game data to understand player’s skill growth through behavior complexity

Abstract

Analysis of game data is used to study player behavior. For puzzle-based games where solutions are usually defined by their action sequences, player behavior can also be studied by their solution complexity. In this paper, we present a visualization system to help learning expert to understand how actions, timing and the resulting strategy change with regard to the solution complexity. To establish a novel perspective into the patterns not only in action choices but also in behavior complexity, we designed an interactive, customized line chart to track how complexity and performance change at each stage of skill acquisition. Specialized glyph system (Strategy Signature) is implemented to find strategy differences easily with simple visual cues. Contextual information can be explored by switching the view modes to see potential links between complexity and raw attributes. Evaluation with expert users shows that the system effectively reduced their time and effort in finding interesting subgroups and gave them unexplored angles of behavior complexity to contemplate player's skill growth. In summary, this paper illustrates a visualization approach to enable analysis into the subtleties of behavior complexity in video games.

Bombalytics: Visualization of Competition and Collaboration Strategies of Players in a Bomb Laying Game

“…Likewise, Li et al [LXC*17] also used timelines to convey concurrent actions of multiple players as part of a larger system to investigate gameplay patterns in multiplayer online battle arena games. Our work shares some similarities with the above works, that is, a) using an action‐centric approach like Osborn et al [OSM18] and b) using a horizontal timeline to represent the timing of actions similar to Li et al [LXC*17, LFLB19]. However, these works take a player‐centric perspective as sequences are visualized independent of other players’ actions.…”

“…Similar play traces are arranged in proximity. Li et al [LFLB19] used a horizontal timeline and plot actions performed by players using color‐coded dots. Likewise, Li et al [LXC*17] also used timelines to convey concurrent actions of multiple players as part of a larger system to investigate gameplay patterns in multiplayer online battle arena games.…”

“…Existing work has employed various sequence mining [KKK14, LJ14] and statistical techniques [Wal15, Hou12] to obtain insights into behavioral sequences. Visualization solutions to help analyze and explore sequences in games are, however, much more scarce (e.g., [OSM18, LFLB19]). These approaches focus on sequences performed by individual players without considering how choices may be based on actions made by teammates or opposing players.…”

Visual Progression Analysis of Event Sequence Data

“…All of the sequences are visualized and aggregated into one interface. Existing techniques adopt various visualization approaches to display event sequences, such as timeline-based [7], [49], [58], [78], [107], [126], sankey-based [111], and hierarchy-based [67], [85], [100], [113] visualizations. Timeline-based visualizations are frequently adopted to reveal temporal information among sequences.…”

Understanding Players’ Interaction Patterns with Mobile Game App UI via Visualizations

“…Visualization is a promising way to enable game experts to dig into deeper the interaction data [15,18,26]. However, most existing visualization tools have long been developed for desktop-based interaction data and cannot be simply borrowed and applied in mobile game scenarios [31,32]. It becomes more challenging when the mobile game app supports intuitive directmanipulation and multi-touch operations, e.g., the joysticks moving towards multiple directions, i.e., up, down, left, right, and different skill buttons possessed by the game character in the app, mimicking real-world metaphors.…”