Mining meaning of videos on YouTube: Unraveling latent content from digital influencers and their engagement
(A2021-93144)

AUTHORS

Eliane Francisco-Maffezzolli, Pontifical Catholic University of Paraná, Curitiba Campus (PUCPR); Ana Cristina Munaro, Pontifícia Universidade Católica do Paraná PUCPR; João Pedro Santos Rodrigues, Pontifícia Universidade Católica do Paraná (PUCPR); Emerson Cabrera Paraiso, Pontifícia Universidade Católica do Paraná (PUCPR)

ABSTRACT

Unstructured data plays a key role in the consumer decision-making process. Advanced techniques for linguistic analysis allow extracting meaning from the content provided by digital influencers. In this paper, we identify the key dimensions of video content on YouTube using a data mining approach, Latent Dirichlet Analysis (LDA). The data set includes 38,427 videos transcript for 103 digital influencers channels over more than 10 years. LDA uncovers 19 content dimensions that remain stable over the past few years on YouTube, highlighting 6 content categories with greater digital engagement: Culture and Entertainment; Family; People, Behavior and Lifestyle; Education; Beauty, and Gastronomy. Dimensions that are key for content creators and professionals to strategically manage their digital engagement with the audience.

REFERENCES

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES).