Visualization of Personal Attributes of YouTubers and Performances of Their Videos

Abstract

Scatterplot matrix is a famous approach for multi-dimensional data visualization that represents a set of arbitrary pairs of dimensions. It has a drawback that a limited number of scatterplots show interesting characteristics of the input datasets. To solve this issue, we have presented a scatterplots selection technique based on multiple metrics of the interestingness of the scatterplots. This paper presents a case study of the technique that assigns personal attributes of YouTubers to the horizontal axes and performances of their videos to the vertical attributes. We discuss the trends and performances of the YouTubers’ videos with the scatterplots selected by our visualization technique.