A carregar...
Publicação
Forecasting TikTok Virality: A Predictive Modeling Approach: Leveraging Text-Based Features to Anticipate Pre-Upload Performance
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 3.19 MB | Adobe PDF |
Orientador(es)
Resumo(s)
TikTok has rapidly emerged as one of the most influential social media platforms
worldwide, driven by its dynamic, personalized recommendation algorithm (the “For
You Page”) and its unique ability to transform ordinary videos into viral successes
almost instantaneously. Despite its widespread popularity, predicting a video’s virality
prior to publication remains a complex challenge, particularly given the platform’s
fast-paced nature and the cultural and linguistic specificity of its user communities.
This research addresses this gap by developing a predictive framework designed to
estimate a video’s virality potential prior to upload, with a particular focus on the
Portuguese-speaking TikTok community. To achieve this, a dataset of TikTok videos
was collected directly from the platform and carefully preprocessed to ensure data
quality and representativeness. By leveraging pre-upload textual features—such as
hashtags, descriptions, and voice-to-text content—informative variables are engineered
and used to train multiple predictive models. During this process, the study also
investigates the dynamics of virality and user engagement behaviors through the
analysis of the impact of the Voice-to-Text feature and the defining characteristics of viral
content. Among the models developed, LightGBM achieves the strongest performance,
sucessfully identifying most viral and non-viral videos in the test set. The findings offer
valuable insights for content creators and marketers seeking to optimize visibility and
engagement, while also contributing to academic understanding of virality in culturally
specific digital contexts.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business Analytics
Palavras-chave
TikTok Virality Prediction Machine Learning Text Mining Voice-to-Text (VTT) Social Media Analytics SDG 4 - Quality education SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure SDG 17 - Partnerships for the goals