# Does a rewritten post title change engagement when the same YouTube video is shared on Reddit, and what text features go with higher engagement?

- id: art_01M5NP96370YAZ91W8BSVDNQQY
- type: article · status: active · revision: 1
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=not_run, review=unreviewed
- categories: T01, T20 · tags: none
- updated: 2026-10-24T00:51:57.153Z
- url: https://veyrul.com/articles/art_01M5NP96370YAZ91W8BSVDNQQY

Problem: separating title wording from video popularity when judging packaging. Conditions: Hu et al. (Georgia Tech, SRI; arXiv 2505.03769, ACM manuscript) built a dataset of 24.1 million Reddit posts linking YouTube videos (19.8M video posts, 12.6M unique videos, 305K subreddits). They report that 21% of post titles are minimally modified from the video title. Method: controlled post pairs sharing the same or similar videos within a 30-minute window, plus an 'inverse' set where the less-popular video's post got more engagement; the mixed controlled set has 86,035 pairs. Measured result: title rewrites measurably relate to engagement; more engaging rewrites tend to show emotional resonance, lexical richness and alignment with community norms; a fine-tuned BERT classifier ranked titles at 74% accuracy in the controlled setting, while GPT-4o was only slightly better than chance. Failure modes: this measures Reddit votes and comments on titles, not YouTube clicks or watch time. Limitat...

Problem: separating title wording from video popularity when judging packaging. Conditions: Hu et al. (Georgia Tech, SRI; arXiv 2505.03769, ACM manuscript) built a dataset of 24.1 million Reddit posts linking YouTube videos (19.8M video posts, 12.6M unique videos, 305K subreddits). They report that 21% of post titles are minimally modified from the video title. Method: controlled post pairs sharing the same or similar videos within a 30-minute window, plus an 'inverse' set where the less-popular video's post got more engagement; the mixed controlled set has 86,035 pairs. Measured result: title rewrites measurably relate to engagement; more engaging rewrites tend to show emotional resonance, lexical richness and alignment with community norms; a fine-tuned BERT classifier ranked titles at 74% accuracy in the controlled setting, while GPT-4o was only slightly better than chance. Failure modes: this measures Reddit votes and comments on titles, not YouTube clicks or watch time. Limitations stated by the authors: a controlled setup may miss ecosystem effects; thumbnails and descriptions are not studied; findings may not generalise beyond Reddit-YouTube pairs. Version/date: arXiv v1, 26 Apr 2025; not reviewed in the form read.

Curator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources.

Limitations: Engagement here is Reddit engagement; effect magnitudes were not extracted; no YouTube view or CTR outcome.

Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.

```json
{
  "citations": [
    {
      "url": "https://arxiv.org/pdf/2505.03769",
      "note": "Abstract; 2 Dataset; Conclusion limits"
    }
  ]
}
```

Evidence claims:
- [sourced_fact] Problem: separating title wording from video popularity when judging packaging. Conditions: Hu et al. (Georgia Tech, SRI; arXiv 2505.03769, ACM manuscript) built a dataset of 24.1 million Reddit posts linking YouTube videos (19.8M video posts, 12.6M unique videos, 305K subreddits). They report that 21% of post titles are minimally modified from the video title. Method: controlled post pairs sharing the same or similar videos within a 30-minute window, plus an 'inverse' set where the less-popular video's post got more engagement; the mixed controlled set has 86,035 pairs. Measured result: title rewrites measurably relate to engagement; more engaging rewrites tend to show emotional resonance, lexical richness and alignment with community norms; a fine-tuned BERT classifier ranked titles at 74% accuracy in the controlled setting, while GPT-4o was only slightly better than chance. Failure modes: this measures Reddit votes and comments on titles, not YouTube clicks or watch time. Limitations stated by the authors: a controlled setup may miss ecosystem effects; thumbnails and descriptions are not studied; findings may not generalise beyond Reddit-YouTube pairs. Version/date: arXiv v1, 26 Apr 2025; not reviewed in the form read. · locator: Abstract; 2 Dataset; Conclusion limits · source: https://arxiv.org/pdf/2505.03769

Rights:
- documentation: license=unknown hosting=permitted redistribution=permitted modification=unknown training=unknown · Applies to this original summary only, not to the cited sources.

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