Statistical patterns in movie ratings

In recent decades, statistical physics has contributed to the study of social dynamics through theoretical models, providing insights and uncovering the crucial laws that govern phenomena such as the spread of information, rumors and opinions.
While there has been notable progress in developing theoretical models,
their validation by direct confrontation with real data has yet to be achieved.
Nowadays, thanks to websites for ratings and recommendations,
new possibilities have arisen to explore this field.
In fact, users and consumers can review and rate products through online services,
which provide huge databases that can be used to explore people's preferences and unveil behavioral patterns.
In this work, we aim to explore patterns in movie rating behavior. As a source of information on the distribution of people's preferences,
we consider IMDb (Internet Movie Database), a highly visited site
worldwide.
The number of votes (where a vote consists of assigning a star rating) rather than, for example, the total number of movie admissions, is a suitable way to measure the popularity of a given movie.
We find that the distribution of votes presents scale-free behavior over several orders of magnitude, with an exponent very close to 3/2, with exponential cutoff.
It is remarkable that this pattern emerges independently of movie attributes such as average rating, age and genre,
with the exception of a few genres and of high-budget films.
These results point to a very general underlying mechanism for the
propagation of adoptions across potential audiences that is
independent of the intrinsic features of a movie and that can be understood through a simple spreading model of avalanche dynamics.