Data Analysis of the Wordle Game: Insights and Predictive Models Based on Twitter Data

Abstract

In 2022, the game "Wordle" gained immense popularity worldwide as players faced the challenge of guessing a five-letter word within six attempts, accompanied by feedback. This paper presents an extensive analysis of "Wordle" based on data mined from Twitter during the period from January 7 to December 31, 2022. The primary objective is to explore the game's dynamics and player engagement comprehensively.To achieve this, a sophisticated time-series model was developed to effectively track the fluctuation in the number of players. The model highlights an initial upward trend, reaching its peak on February 3, followed by a gradual decline and eventual stabilization, reflecting the sustained allure of the game. Additionally, this paper leveraged an XGBoost model to predict the distribution of player attempts, exhibiting remarkable accuracy, particularly for attempts ranging from three to six. This research demonstrates the powerful impact of data science in decoding intricate game dynamics and player behavior. Moreover, it emphasizes the fusion of gaming, data analytics, and social media as an exciting frontier for future research. The study's findings provide valuable insights into the gaming community's preferences and the underlying mechanisms that drive user engagement in digital gaming platforms.