Players increasingly adopt a data-driven approach to review and improve their gaming skills. In the wake of this, spatio-temporal visualizations gained popularity but remain challenging to design. Storyline visualizations are unique in the way they integrate time and location information into a single view to show how entity relationships develop over time. We adopt the storyline visualization technique to summarize gameplay for the purpose of post-play review.
For more details, check our paper.
As for now, this web app supports visualizing the following information:
- Basic player information (which champion is used for which team)
- Players' positions in 1 minute intervals
- Players' kills and deaths
- Tower kills
- Areas on a map reflected on y-axis (e.g. jungle)
This app would also allow user to get detailed information of each event by hovering over the event/storylines. An example of storyline visualization for a League of Legends match is shown below:
Use the package manager npm or yarn to install iStoryline.
npm install i-storyline-js
or
yarn add i-storyline-js
import iStoryline from "i-storyline-js"
let iStoryliner = new iStoryline();
// generate storyline visualizations from the story script
let storyScriptUrl = './data/xml/Redcap.xml';
// graph can be drawed using any canvas or svg libraries
let graph = iStoryliner.load(storyScriptUrl);
// obtain the characters names
console.log(graph.characters); // ['Red cap', 'Mother', 'Wolf', 'GrandMa']
// obtain the paths of the characters
console.log(graph.storylines); // [[[x1, y1], [x2, y2], ...], ...]
First using our python project to fetch the match data and convert it into a storyline json file. This will ultimately gives you match spatio-temporal data, general match information file, a killing info file and a DBSCAN result. For this, check our Lol_Storyline Data project and follow the instructions there.
You should put your visualization instance javascript file under the /app/js
folder. You should also check the /data/json/Match
folder to see the data files that are used in the storyline visualisation.
To create a new match visualization instance, you can start copying one file from the /app/js
folder, rename it and make changes as following:
// adding match info to the storyline (fetched from Riot API)
const jsonRead = d3Fetch.json('../../data/json/xxx.json')
// adding killing info file generated by python
const jsonReadTwo = d3Fetch.json('../../data/json/xxx.json')
// adding DBSCAN result file generated by python
const jsonDBSCAN = d3Fetch.json('../../data/json/xxx.json')
// adding the match data generated by python for parsing
main('xxx.json');
Please then check and modify the webpack config file for new entry.
iStoryline.js provides a build-in editor for producing storyline visualizations.
-
Install Node.js (>= 10.0)
-
Install dependencies
npm i
oryarn
-
Start the editor
npm run start
-
Please visit localhost:8080
- G. Wallner, L. Wang, and C. Dormann. "Visualizing the Spatio-Temporal Evolution of Gameplay using Storyline Visualization: A Study with League of Legends. Proc. ACM Hum.-Comput. Interact.", 7(CHI PLAY):412, 2023.
- T. Tang, S. Rubab, J. Lai, W. Cui, L. Yu, and Y. Wu. "iStoryline: Effective Convergence to Hand-drawn Storylines. IEEE Transactions on Visualization and Computer Graphics", 25(1):769-778, 2019.
- S. Liu, Y. Wu, E. Wei, M. Liu, and Y. Liu. "StoryFlow: Tracking the Evolution of Stories. IEEE Transactions on Visualization and Computer Graphics", 19(12):2436–2445, 2013.
We appreciate your citation if this GitHub repo contributes to your work.
@article{10.1145/3611058,
author = {Wallner, G\"{u}nter and Wang, Letian and Dormann, Claire},
title = {Visualizing the Spatio-Temporal Evolution of Gameplay using Storyline Visualization: A Study with League of Legends},
year = {2023},
issue_date = {November 2023},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {7},
number = {CHI PLAY},
url = {https://doi.org/10.1145/3611058},
doi = {10.1145/3611058},
abstract = {Players increasingly adopt a data-driven approach to review and improve their gaming skills. In the wake of this, spatio-temporal visualizations gained popularity but remain challenging to design. Storyline visualizations are unique in the way they integrate time and location information into a single view to show how entity relationships develop over time. We adopt the storyline visualization technique to summarize gameplay for the purpose of post-play review. We demonstrate the method by applying it to League of Legends matches and evaluated it with 39 players of the game in a task-based online study using the triad framework for spatio-temporal queries by Peuquet. Results indicate that players responded positively to the approach and could, by and large, solve tasks well but that time-based tasks proved most challenging and least efficient to solve. Based on our findings, we reflect on possibilities for enhancing the design of storyline visualizations for game-related data analysis.},
journal = {Proc. ACM Hum.-Comput. Interact.},
month = {oct},
articleno = {412},
numpages = {23},
keywords = {League of Legends, Player-centric visualization, match analysis, storyline visualization}
}
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