Abstract
Engaging in playful activities, such as playing a musical instrument, learning a language, or performing sports, is a fundamental aspect of human life. We present a quantitative empirical analysis of the engagement dynamics into playful activities. We do so by analyzing the behavior of millions of players of casual video games and discover a scaling law governing the engagement dynamics. This power-law behavior is indicative of a multiplicative (i.e., “happy- get-happier”) mechanism of engagement characterized by a set of critical exponents. We also find, depending on the critical exponents, that there is a phase transition between the standard case where all individuals eventually quit the activity and another phase where a finite fraction of individuals never abandon the activity. The behavior that we have uncovered in this work might not be restricted only to human interaction with videogames. Instead, we believe it reflects a more general and profound behavior of how humans become engaged in challenging activities with intrinsic rewards.
Highlights
Engaging in playful activities, such as playing a musical instrument, learning a language, or performing sports, is a fundamental aspect of human life
It is not our intention to enter into the psychological, motivational, behavioral, or social aspects of video game playing nor criticize the standard psychometric, behavioral or physiological metrics, or questionnaire-based evaluation of engagement performed on a limited number of individuals and short time span
We have focused on the particular case of engagement in videogames since, to the best of our knowledge, it is the only system where the amount of available data allows us to elucidate sound statistical laws
Summary
Engaging in playful activities, such as playing a musical instrument, learning a language, or performing sports, is a fundamental aspect of human life. We do so by analyzing the behavior of millions of players of casual video games and discover a scaling law governing the engagement dynamics. Before the new era of modern technology, answering this type of question relied on the accumulated knowledge obtained from qualitative observations of single individuals made in different conditions by different observers This makes it very difficult to extract general laws of human behavior. In some of the games we have analyzed, we follow the individual behavior of a cohort of 10 million players during a period of two years This astonishing amount of data allows us to quantify empirically users’ engagement vs progression in a way that has not been possible before the big data era. Our analysis reveals a scaling law that is universal –across many different games, player segmentation, or countries– with profound theoretical implications
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