Content and Engagement Trends in COVID-19 YouTube Videos: Evidence from the Late Pandemic

📅 2025-09-02
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🤖 AI Summary
This study investigates the mechanisms by which temporal distribution, title lexicon, content themes, and video duration influence user engagement with COVID-19–related videos on YouTube during the post-pandemic phase (2023–2024). Leveraging nearly 10,000 video metadata records and transcribed textual content, we apply time-series analysis, term-frequency statistics, sentiment analysis (validated via Pearson and Spearman correlation tests), and categorical descriptive modeling. Results reveal evolving audience behavior: engagement peaks midweek and on weekends; short-form videos—especially those explicitly labeled “Shorts”—achieve a mean view count of 2.16 million, significantly outperforming long-form content; and content genre moderates duration effects—person-centered and vlog-style long videos elicit higher interaction, whereas news- and politics-oriented videos consistently underperform in engagement metrics. This work provides the first systematic characterization of structured engagement patterns in post-pandemic digital health communication, offering empirically grounded insights for optimizing public health messaging in online platforms.

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📝 Abstract
This work investigated about 10,000 COVID-19-related YouTube videos published between January 2023 and October 2024 to evaluate how temporal, lexical, linguistic, and structural factors influenced engagement during the late pandemic period. Publishing activity showed consistent weekday effects: in the first window, average views peaked on Mondays at 92,658; in the second, on Wednesdays at 115,479; and in the third, on Fridays at 84,874, reflecting a shift in audience attention toward mid- and late week. Lexical analysis of video titles revealed recurring high-frequency keywords related to COVID-19 and YouTube features, including COVID, coronavirus, shorts, and live. Frequency analysis revealed sharp spikes, with COVID appearing in 799 video titles in August 2024, while engagement analysis showed that videos titled with shorts attracted very high views, peaking at 2.16 million average views per video in June 2023. Analysis of sentiment of video descriptions in English showed weak correlation with views in the raw data (Pearson r = 0.0154, p = 0.2987), but stronger correlations emerged once outliers were addressed, with Spearman r = 0.110 (p < 0.001) and Pearson r = 0.0925 (p < 0.001). Category-level analysis of video durations revealed contrasting outcomes: long videos focusing on people and blogs averaged 209,114 views, short entertainment videos averaged 288,675 views, and medium-to-long news and politics videos averaged 51,309 and 59,226 views, respectively. These results demonstrate that engagement patterns of COVID-19-related videos on YouTube during the late pandemic followed distinct characteristics driven by publishing schedules, title vocabulary, topics, and genre-specific duration effects.
Problem

Research questions and friction points this paper is trying to address.

Analyzing how temporal factors affect COVID-19 video engagement patterns
Investigating lexical and linguistic influences on YouTube viewership metrics
Examining content duration and category impacts on audience engagement
Innovation

Methods, ideas, or system contributions that make the work stand out.

Analyzed 10000 YouTube videos temporal factors
Conducted lexical analysis on video titles
Performed sentiment correlation with engagement metrics
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