Visualizing the Spatio-Temporal Evolution of Gameplay using Storyline Visualization: A Study with...
summary
A storyline visualization for League of Legends is built from Riot API position logs, clustering consecutive kills into group fights and mapping map regions to y-axis lanes; the prototype uses regular one-minute sampling and tooltips for events. A lab-style online study with 39 participants and 12 triad tasks (Peuquet’s where/when/what) shows players solve “what” and “where” tasks well but struggle with “when”, efficiency drops for time queries, and number of locations does not affect accuracy; visual clutter from simultaneous area changes remains a clear limitation.
AI-written summary · about
related talks
14mModeling Individual and Team Behavior through Spatio-temporal Analysis
17mWhat Moves Players? Visual Data Exploration of Twitter and Gameplay Data
35mDecoding bias and narrative in competitive video games
01h 27mLeveling Up Your Storytelling and Visualization Skills
08m"Trust the Process'': An Exploratory Study of Process Visualizations for Self-Reflection in Leagu...
16mUser Guided Movement Analysis in Games using Semantic Trajectories
02mStreaks and Coping: Decoding Player Performance in League of Legends Using Big Data from Top Play...
30mData Storytelling through Visualization