Mining and modelling temporal dynamics of followers’ engagement on online social networks

Abstract

A relevant fraction of human interactions occurs on online social networks. In this context, the freshness of content plays an important role, with content popularity rapidly vanishing over time. We therefore investigate how influencers’ generated content (i.e., posts) attracts interactions, measured by the number of likes or reactions. We analyse the activity of influencers and followers over more than 5 years, focusing on two popular social networks: Facebook and Instagram, including more than 13 billion interactions and about 4 million posts. We investigate the influencers’ and followers’ behaviour over time, characterising the arrival process of interactions during the lifetime of posts, which are typically short-lived. After finding the factors playing a crucial role in the post popularity dynamics, we propose an analytical model for the user interactions. We tune the parameters of the model based on the past behaviour observed for each given influencer, discovering that fitted parameters are pretty similar across different influencers and social networks. We validate our model using experimental data and effectively apply the model to perform early prediction of post popularity, showing considerable improvements over a simpler baseline.

Divulgación de la literatura infantil a través de cuentas de influencers en Instagram: factores que influyen en el nivel de engagement

“…El desarrollo de las redes sociales es veloz y exponencial, lo cual provoca que aún no se tenga una correcta conciencia de la dinámica temporal de los mensajes ni de las interacciones (Vassio et al, 2022). Además, este crecimiento se está produciendo sin ninguna organización ni estructura, ya que la presencia de los medios y las tecnologías en los centros educativos "no está sistematizada, ni se ha producido de forma racionalizada" (Pérez-Rodríguez y Delgado-Ponce, 2012, p. 26).…”