Investigation of Benford’s Law with YouTube Social Media Statistics
Keywords:Curve Fitting, Mathematical Model, Benford’s Law, Social Media
In this study, we used social media data to investigate Benford’s Law. In our experimental analysis, we used three control variables: Total Subscriptions, Total Views, and Video Uploads of Youtube channels to verify if the data is artificial and whether or not it fits Benford’s Law. We noticed how Total Subscriptions does not fit Benford’s Law for the top 5000 most-subscribed channels, and Total Views doesn’t fit for the top 5000 most-viewed channels. The reasons that cause this difference are further investigated in this paper. We also proposed a mathematical model to verify if other datasets fit Benford’s Law. After curve fitting the experimental data, results revealed that closer a and b values in our mathematical model indicate that a dataset fits Benford’s Law.
References or Bibliography
Chi-Wei is a high school junior, an experienced programmer, and a prospective Computer Science student in college. Outside of the classroom, Chi-Wei is passionate about inspiring other young learners by spreading STEM knowledge to underprivileged children through LEGO EV3, English, and programming classes. Driven by his passion for solving real-world problems with his STEM knowledge, he seeks to build creative solutions to problems, such as the identification of true and false data, in this information-filled era.
Shao-Yu Yu is a high-school student who studies in Taipei Fuhsing Private School. Shao-Yu is the captain of his school’s FRC team and the team has won numerous awards in the robotics competition. He is a student that shows incredible passion in the STEAM field and has just learned about Benford’s Law on the internet, and as a high-school student, Shao-Yu spends a fair amount of time on social media. With the knowledge of Benford’s Law, he starts to wonder how Benford’s Law works on the data in regards of social media rankings.
How to Cite
Copyright (c) 2021 Chi-Wei Chen, Shao-Yu Yu; Hsin-Yi Chen
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright holder(s) granted JSR a perpetual, non-exclusive license to distriute & display this article.