Museums on Social Media: analyzing growth and information spread through case studies

Paper
Alex Espinós, La Magnética, Spain

Published paper: Museums on social media: Analyzing growth through case studies

During the Baltimore and Florence conferences, we presented our report on how two thousand museums worldwide related on Twitter. We analyzed the most influential museums on Twitter, the factors underlying the observed community structure, the evolution of museums’ Twitter use, and the museums that worked as a hub.

Last year we focused on three case studies about the relationship between a museum and its followers and how to use this information to design better social media strategies. This year, we focus the last part of this three-year-long research on two key points:
1) The growth of a museum’s community in social media: causal factors, quantitative and qualitative issues
2) Factors explaining the spread of information across the network

There are several aspects that make a museum’s presence on social media different than that of a company, and these factors have an impact on follower growth and on the spread of information. The foremost of these factors are:
 The lack of advertisement budget: even those lucky museums that have a social media advertisement budget lack the resources to base their growth on ads
 The collaborative environment
 The engagement that followers establish with the museum on social media

We will run quantitative and qualitative research focused on gaining insights to improve museums’ social media strategies through a more informed decision-making process and throughout analysis.

Through several different case studies, we are going to analyze the real weight that this and several other factors have. What are the factors limiting a museum’s real reach or growth on social media? Which percentage of a museum follower’s growth can be attributed to this (and other) mechanisms? Which implications does it have for defining successful social media strategies?

As in previous papers, big data and advanced mathematics are going to be used, but the final paper will be nontechnical and focused on the insights museums can get from this research.

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