A Network Analysis of Museums on Instagram

Instagram, the photo and video sharing social network platform, has enjoyed exponential growth since its launch. As Instagram’s popularity is growing fast, museums are moving quickly to integrate it into their marketing strategies, provide information about exhibitions and objects, engage with audience and connect to other museums Instagram accounts. This paper aims at investing the interconnections among the Instagram accounts of the most visited museums worldwide. The analysis uses techniques from Social Network Analysis, including visualization algorithms and calculations of well-established metrics. The research shows that the network formed by the museum Instagram accounts is a scale-free small world network and reveals the most important nodes of the network. Depending or their marketing policies, other museums may follow the most important in the network, be aware of the information that flows in the network and also to be motivated and inspired by them.

[1]  Dimitrios Kydros.  Twitting bad rumours - the grexit case , 2018, Int. J. Web Based Communities.

[2]  Jim Angus,et al.  Innovations in Practice , 2012 .

[3]  Dale Schuurmans,et al.  Modular Community Detection in Networks , 2011, IJCAI.

[4]  Kylie Budge.  Objects in Focus: Museum Visitors and Instagram , 2017 .

[5]  Mathieu Bastian,et al.  Gephi: An Open Source Software for Exploring and Manipulating Networks , 2009, ICWSM.

[6]  Performance of public-private collaborations in advanced technology research networks : network analyses of Genome Canada projects , 2007 .

[7]  A. Anastasiadis,et al.  Greek Political Language during the Economic Crisis—A Network Analytic Approach , 2017 .

[8]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[9]  Jenny Kidd,et al.  Enacting engagement online: framing social media use for the museum , 2011, Inf. Technol. People.

[10]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Kydros Dimitrios,et al.  A Network Analysis of the Greek Stock Market , 2015 .

[12]  Réka Albert,et al.  correction: Error and attack tolerance of complex networks , 2001, Nature.

[13]  Efthymios Constantinides,et al.  Social Media: A New Frontier for Retailers? , 2008 .

[14]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[15]  Konstantinos Antoniadis,et al.  Sharing Followers in e-Government Twitter Accounts: The Case of Greece , 2014, Future Internet.

[16]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[17]  Amalya L. Oliver,et al.  Social Networks, Learning, and Flexibility: Sourcing Scientific Knowledge in New Biotechnology Firms , 1994 .

[18]  Kylie Budge,et al.  Museum objects and Instagram: agency and communication in digital engagement , 2018 .

[19]  A. Suess.  Instagram and art gallery visitors: Aesthetic experience, space, sharing and implications for educators , 2018 .

[20]  Adrienne Fletcher,et al.  Current social media uses and evaluations in American museums , 2012 .

[21]  Qiang Wang,et al.  Topic oriented community detection through social objects and link analysis in social networks , 2012, Knowl. Based Syst..

[22]  Thomas Hillman,et al.  Instagram at the museum: communicating the museum experience through social photo sharing , 2013, CHI.

[23]  B. Wellman.  Computer Networks As Social Networks , 2001, Science.

[24]  Subbarao Kambhampati,et al.  What We Instagram: A First Analysis of Instagram Photo Content and User Types , 2014, ICWSM.

[25]  Albert-László Barabási,et al.  Error and attack tolerance of complex networks , 2000, Nature.

[26]  M. Osterman,et al.  Museums and Twitter: An Exploratory Qualitative Study of How Museums Use Twitter for Audience Development and Engagement , 2012 .

[27]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.