Please use this identifier to cite or link to this item:
https://digital.lib.ueh.edu.vn/handle/UEH/78300Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Cong Van Tran | - |
| dc.contributor.author | Khoi Minh Nguyen | - |
| dc.contributor.author | Phuong Thanh Thai | - |
| dc.contributor.author | Hoai Thi Thu Le | - |
| dc.contributor.author | Minh Thi Hong Le | - |
| dc.contributor.author | Thinh Thai Dang | - |
| dc.date.accessioned | 2026-07-07T07:10:27Z | - |
| dc.date.available | 2026-07-07T07:10:27Z | - |
| dc.date.issued | 2026 | - |
| dc.identifier.isbn | 9783032077202; 9783032077219 | - |
| dc.identifier.uri | https://digital.lib.ueh.edu.vn/handle/UEH/78300 | - |
| dc.description.abstract | This analysis examined the disparity between AI and human TikTok videos with respect to user engagement utilizing sentiment analysis and topic modeling. The study collected a sample of 400 TikTok videos alongside 255,541 comments to gauge sentiment dispersion and talk disregarding themes AI versus human content. Results suggested a neutral comment sentiment towards the AI content while the human content achieved deeper emotional engagement along with stronger positive sentiment comment and criticisms. The study was built on media richness theory by adding that within the context of engagement, authenticity preempts the impact of technical quality. This study also was conducted two contrasting user motivations for AI versus human content. As a result, content creators should make use of AI’s efficiency while appealing to human emotional charge in order to achieve greater engagement. | en |
| dc.language.iso | eng | - |
| dc.publisher | Springer | - |
| dc.relation.ispartof | From Smart Cities to Smart Factories for a Sustainable Future | - |
| dc.rights | Springer Nature | - |
| dc.subject | User engagement | en |
| dc.subject | AI-generated content | en |
| dc.subject | Human-generated content | en |
| dc.subject | Sentiment analysis | en |
| dc.subject | SDG 12 (Responsible Consumption and Production) | en |
| dc.title | What Drives Engagement? Analyzing Comment Sentiment and Discussion Themes in AI- and Human-Generated TikTok Content Using Sentiment Analysis | en |
| dc.type | Book chapter | en |
| dc.identifier.doi | https://doi.org/10.1007/978-3-032-07721-9_68 | - |
| dc.format.firstpage | 765 | - |
| dc.format.lastpage | 773 | - |
| item.openairetype | Book chapter | - |
| item.languageiso639-1 | en | - |
| item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
| item.cerifentitytype | Publications | - |
| item.fulltext | Only abstracts | - |
| item.grantfulltext | none | - |
| Appears in Collections: | INTERNATIONAL PUBLICATIONS | |
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