Wordle Visualization

Vedanshi Shah, Haleluya Asfaw, Bayden Ibrahim, Isobelle Lim, Luca Sharbani

Course Project as part of DS4200 S22: Information Visualization, taught by Prof. Ab Mosca, Data Visualization @ Khoury, Northeastern University.

Abstract

Wordle is a popular daily word-guessing game that has become a viral sensation for its simple premise of guessing a five letter word in six attempts. Despite its solo-style play, it has fostered a competitive community. The game provides individual scores but lacks overall game-wide statistics, so trends like overall performance and relative difficulty are not available. Our project aims to make these analyses possible in a visualization that not only captures data about the players, but also the game itself.
Keywords: Linguistics, word puzzle, player performance.
https://github.com/DS4200-S22/final-project-wordle_visualization

Visualization

Demo Video

Below is our demonstration video to walk through the Wordle visualization we created.

If your browser doesn't support HTML5 video. Here is a link to the video instead.

Visualization Explanation

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The link to our presentation slides can be found here: Presentation Slides

Our final visualization tool contains a line graph showing number of players every day, a word cloud that shows every day’s word, and a temporal bar graph. A user can choose whether or not to form the word cloud based on word rarity or player performance. While the word cloud responds to whatever the user chooses, say rarity, the bar graph also responds by forming to be based on the opposite, in this case performance. Both of these views individually stand with a basic tooltip that allows the user to see details upon hovering. However, these two views are also linked, such that the user can hover over any part and see its corresponding bar metric or word in the other view. There is a dynamic legend that also aids to discern what the different channels mean, and additionally, when the user hovers, an additional blub appears above with more details about that days’ statistics. Wrapping this entire thing is a brushing capability in the line graph where highlighting a certain area narrows the focus of all of the other views, correspondingly.

Final Paper

The link to our paper can be found here: Final Paper

Acknowledgments

Add to think list citations for any code, packages/libraries, text, images, designs, etc. that you leveraged.

• Word Cloud Layout by Jason Davies was used in part to create the word cloud.
• d3 Graph Gallery was used to create the donut chart.
• Responsive Slideshow Tutorial by W3Schools was used to embed our project slideshow.
• Sanderson, G. (2022). Solving Wordle using information theory. 3Blue1Brown. Retrieved February 23, 2022, from https://www.3blue1brown.com/lessons/wordle
• John, M., Marbach, E., Lohmann, S., Heimerl, F., & Ertl, T. (2018). MultiCloud: Interactive Word Cloud Visualization for the Analysis of Multiple Texts [Review of MultiCloud: Interactive Word Cloud Visualization for the Analysis of Multiple Texts]. Proceedings of the 44th Graphics Interface Conference, 18th. https://doi.org/https://doi.org/10.20380/GI2018.06
• Li, W., Funk, M., Li, Q. et al. Visualizing event sequence game data to understand player’s skill growth through behavior complexity. J Vis 22, 833–850 (2019). https://doi.org/10.1007/s12650-019-00566-5
• Moura, D., el-Nasr, M. S., & Shaw, C. D. (2011). Visualizing and understanding players' behavior in video games. Proceedings of the 2011 ACM SIGGRAPH Symposium on Video Games - Sandbox '11. https://doi.org/10.1145/2018556.2018559
• Morgan, C. L., & Bonham, D. N. (1944). Difficulty of vocabulary learning as affected by parts of speech. Journal of Educational Psychology, 35(6), 369–377. https://doi.org/10.1037/h0059537
• Wordle tweets. (n.d.). Kaggle: Your Machine Learning and Data Science Community. https://www.kaggle.com/benhamner/wordle-tweets
• Wordle Stats. (2022, January). Wordle Stats. twitter.com. https://twitter.com/wordlestats
• Getting started with the Twitter API. (n.d.). Use Cases, Tutorials, & Documentation | Twitter Developer Platform. https://developer.twitter.com/en/docs/twitter-api/getting-started/about-twitter-api#v2-access-level
• Google Ngram exports. (n.d.). https://storage.googleapis.com/books/ngrams/books/datasetsv3.html
• Datamuse API. (n.d.). https://www.datamuse.com/api/