A relevant fraction of human interactions occurs on online social networks. Freshness of content seems to play an important role, with content popularity rapidly vanishing over time. In this paper, we investigate how influencers' generated content (i.e., posts) attracts interactions, measured by number of likes or reactions. We analyse the activity of Italian 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 characterise the influencers' and followers' behaviour over time, show that influencers' posts are short-lived with an exponential temporal decay, and characterise the time evolution of the interactions from their initial peak till the end of a post lifetime. Finally, leveraging our findings, we discuss how they can be exploited to develop an analytical model of the interactions temporal dynamics.

Temporal Dynamics of Posts and User Engagement of Influencers on Facebook and Instagram / Vassio, Luca; Garetto, Michele; Chiasserini, Carla Fabiana; Leonardi, Emilio. - STAMPA. - (2021), pp. 129-133. (Intervento presentato al convegno 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) tenutosi a Virtual Event, Netherlands nel November 8–11, 2021) [10.1145/3487351.3488340].

Temporal Dynamics of Posts and User Engagement of Influencers on Facebook and Instagram

Luca Vassio;Carla Chiasserini;Emilio Leonardi
2021

Abstract

A relevant fraction of human interactions occurs on online social networks. Freshness of content seems to play an important role, with content popularity rapidly vanishing over time. In this paper, we investigate how influencers' generated content (i.e., posts) attracts interactions, measured by number of likes or reactions. We analyse the activity of Italian 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 characterise the influencers' and followers' behaviour over time, show that influencers' posts are short-lived with an exponential temporal decay, and characterise the time evolution of the interactions from their initial peak till the end of a post lifetime. Finally, leveraging our findings, we discuss how they can be exploited to develop an analytical model of the interactions temporal dynamics.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2927596