The preliminary findings from the linear regression analysis (Table 1) suggest a meaningful relationship between the online engagement metrics of videos on YouTube and the academic impact of the publications referenced within these videos. Specifically, the analysis found positive correlations with the citation impact for three key metrics: the number of videos referencing publications, the ratio of likes to dislikes on videos, and the number of comments containing references to other publications. The positive correlation indicates a sort of selective amplification process. Publications mentioned in videos that garner attention in the form of likes and active discussion in comments are likely being selectively chosen for their relevance or quality. This selection process by content creators and the subsequent engagement by viewers may serve as an “informal peer review”, signaling the value and impact of the research. The findings suggest that social media, particularly YouTube in this context, acts as a filter that potentially can highlight the visibility of impactful research.
https://arxiv.org/abs/2405.12734
| Artificial Intelligence |
| Research Data Curation and Management Works |
| Digital Curation and Digital Preservation Works |
| Open Access Works |
| Digital Scholarship |
