Does a rewritten post title change engagement when the same YouTube video is shared on Reddit, and what text features go with higher engagement?
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...
Structured fields
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"citations": [
{
"url": "https://arxiv.org/pdf/2505.03769",
"note": "Abstract; 2 Dataset; Conclusion limits"
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}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
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| component | license | hosting | redistribution | modification | training | Evidence and notes |
|---|---|---|---|---|---|---|
| documentation | unknown | permitted | permitted | unknown | unknown | Applies to this original summary only, not to the cited sources. |
Linked records
- cites → https://arxiv.org/pdf/2505.03769