Difference between revisions of "The Untold Story of the Clones: Content-agnostic Factors that Impact YouTube Video Popularity"
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− | This paper develops and applies a methodology for assessing the impacts of various content-agnostic factors (e.g. total view counts, uploader followers, video age, etc.) on video popularity. To evaluate the relative influence of different factors, three statistical tools are used: 1) PCA for grouping of variables responsible for the popularity variation, 2) Correlation and collinearity analysis for identifying interrelated variables, and 3) Multi-linear regression with variable selection for identifying most informative variables. The dataset they used contains 48 clone sets of Youtube videos with three types of information: video statistics, historical view count, and influential events. | + | This paper develops and applies a methodology for assessing the impacts of various content-agnostic factors (e.g. total view counts, uploader followers, video age, etc.) on video popularity. To evaluate the relative influence of different factors, three statistical tools are used: 1) PCA for grouping of variables responsible for the popularity variation, 2) Correlation and collinearity analysis for identifying interrelated variables, and 3) Multi-linear regression with variable selection for identifying most informative variables. The dataset they used contains 48 clone sets of Youtube videos with three types of information: video statistics, historical view count, and influential events. Some of the most important findings from their analysis on Youtube videos include: 1) Inaccurate conclusions may be reached when not controlling for video content; 2) Total view count is the most important explanatory variable except for very young videos; 3) Content-agnostic factors can also help explain the popularity dynamics to some extent; and 4) There's strong advantage in video popularity for first movers. |
== Results == | == Results == | ||
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== Related Papers == | == Related Papers == | ||
== Study Plan == | == Study Plan == |
Revision as of 20:12, 2 November 2012
Online Version
An electronic version of this paper can be downloaded here: [1]
Summary
This paper develops and applies a methodology for assessing the impacts of various content-agnostic factors (e.g. total view counts, uploader followers, video age, etc.) on video popularity. To evaluate the relative influence of different factors, three statistical tools are used: 1) PCA for grouping of variables responsible for the popularity variation, 2) Correlation and collinearity analysis for identifying interrelated variables, and 3) Multi-linear regression with variable selection for identifying most informative variables. The dataset they used contains 48 clone sets of Youtube videos with three types of information: video statistics, historical view count, and influential events. Some of the most important findings from their analysis on Youtube videos include: 1) Inaccurate conclusions may be reached when not controlling for video content; 2) Total view count is the most important explanatory variable except for very young videos; 3) Content-agnostic factors can also help explain the popularity dynamics to some extent; and 4) There's strong advantage in video popularity for first movers.