Triangulating research discourse on tiktok: integrating bibliometrics, sentiment analysis and topic modeling

This paper investigates the academic discourse surrounding TikTok, the globally influential short-video social media platform, with a particular focus on its relationship with politics (accounting for 24.7% of the total papers). It aims to uncover trends, entities and links within TikTok-related research, addressing broader topics on the platform’s impact and narrower themes involving its political implications. Using bibliometric analysis of 2,313 publications indexed in the Web of Science (2019–2024), our research employs a dual framework combining sentiment analysis and topic modeling. To ensure robustness and capture complementary perspectives, we apply three sentiment analysis approaches alongside three topic modeling approaches (LDA, BERT-LDA, BERT-Clustering). This multi-method strategy enables us to cross-validate findings, highlight convergences and expose different nuances. The three approaches share overlapping themes but vary in scope and depth. The analyses reveal rising negativity and declining positivity over time, with peaks in negativity in the recent years: 2023 and 2024. Positive sentiment was highest in 2019 but steadily declined, while all methods highlight increasing critical sentiment and less emotional polarization in recent years. Key findings reveal significant trends in TikTok’s societal, cultural and political influence, highlighting its role in shaping public opinion, amplifying misinformation and influencing democratic processes.