How to quantify social media influencers: An empirical application at the Teatro alla Scala

Deborah Agostino, Michela Arnaboldi, Anna Calissano

Heliyon · 2019 · 58 citations · 34 references

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TL;DR

Identifying and appraising social media influencers is crucial for organizations because they shape online conversations, yet research has largely overlooked the extent of their influence. The study aims to quantify and classify SMIs using K‑shell decomposition and examine how each influencer type affects an organization’s public relations. The authors applied the K‑shell decomposition method in an action‑research project at Milan’s Teatro alla Scala, then discussed the results with the opera house’s management. The analysis revealed that SMIs can be categorized as writers, authorities, or spreaders, providing a focused typology that both advances academic understanding and offers managers a practical tool for analytics.

Abstract

A topic of primary importance for organizations is the ability to identify and appraise Social Media Influencers (SMIs), given their key role in affecting conversations and interactions on social media. According to the current research in this area, influencers make up a single category of social media users, but only limited attention has been paid concerning the extent to which they can exert their influence. In this study, the quantification and classification of SMIs is addressed by proposing an advanced methodology based on social network analysis - K-shell decomposition - together with a discussion on the relationship between the different SMI categories and the effect of each type of influencer on the public relation activity of an organization. The developed methodology was tested through an action research project conducted at the Teatro alla Scala of Milan, and the results were then discussed with the management of the opera house. The main finding of this work is that SMIs can be split into writers, authorities or spreaders on the basis of the kind of influence they exert, thereby delivering a precisely focused typology of SMIs. These findings enhance our academic knowledge on analytics applied to social science, while also providing a real case situation where managers make practical use of analytics.

References

34