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Shorts vs. Regular Videos on YouTube: A Comparative Analysis of User Engagement and Content Creation Trends

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arxiv 2403.00454 v1 pith:777EFNYE submitted 2024-03-01 cs.SI

classification cs.SI
keywords shortsvideosregularcategoriescontentyoutubeanalysisattract
verification ladder T0 review T1 audit T2 compute T3 formal
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YouTube introduced the Shorts video format in 2021, allowing users to upload short videos that are prominently displayed on its website and app. Despite having such a large visual footprint, there are no studies to date that have looked at the impact Shorts introduction had on the production and consumption of content on YouTube. This paper presents the first comparative analysis of YouTube Shorts versus regular videos with respect to user engagement (i.e., views, likes, and comments), content creation frequency and video categories. We collected a dataset containing information about 70k channels that posted at least one Short, and we analyzed the metadata of all the videos (9.9M Shorts and 6.9M regular videos) they uploaded between January 2021 and December 2022, spanning a two-year period including the introduction of Shorts. Our longitudinal analysis shows that content creators consistently increased the frequency of Shorts production over this period, especially for newly-created channels, which surpassed that of regular videos. We also observe that Shorts target mostly entertainment categories, while regular videos cover a wide variety of categories. In general, Shorts attract more views and likes per view than regular videos, but attract less comments per view. However, Shorts do not outperform regular videos in the education and political categories as much as they do in other categories. Our study contributes to understanding social media dynamics, to quantifying the spread of short-form content, and to motivating future research on its impact on society.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Investigating Algorithmic Bias in YouTube Shorts

    cs.SI 2025-07 reject novelty 4.0 of 10

    YouTube Shorts recommendations from political seeds drift to entertainment and positive-emotion content within the first few steps, with the drift unchanged by simulated watch-time.

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