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Museum Twitter ecosystem (Social Network Analysis). LaMagnética

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Information about Museum Twitter ecosystem (Social Network Analysis). LaMagnética
Social Media

Published on February 19, 2014

Author: ComunicacionLaMagnetica

Source: slideshare.net

Description

Do Museums Worldwide form a true Community on Twitter?

Some insights on the museum Twitter ecosystem through Social Network Analysis and Network Science.

International conference: Museums and the web, 2014. Florence (Italy) and Baltimore, MD (USA).
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Alex Espinós ~ alex@lamagnetica.com Marc Espín ~ marc@lamagnetica.com

___ Do Museums Worldwide form a true Community on Twitter? Some insights on the museum Twitter ecosystem through Social Network Analysis and Network Science. { {

The Museum ecosystem on Twitter The study Why this study? Questions we want to answer Methodology Introduction Introduction Conclusions 1

The Museum ecosystem on Twitter Conclusions The study Introduction > Why this study?

The Museum ecosystem on Twitter > Why this study? The study Conclusions The new paradigm of communication that Social Networks have brought Introduction Everybody talks about things like:

The Museum ecosystem on Twitter > Why this study? The study Knowledge and experience sharing Conclusions The new paradigm of communication that Social Networks have brought Introduction Everybody talks about things like:

The Museum ecosystem on Twitter > Why this study? Information flow The study Knowledge and experience sharing Conclusions The new paradigm of communication that Social Networks have brought Introduction Everybody talks about things like:

The Museum ecosystem on Twitter > Why this study? Everybody talks about things like: Information flow Introduction The study Knowledge and experience sharing Conclusions The new paradigm of communication that Social Networks have brought User feedback

The Museum ecosystem on Twitter > Why this study? Conclusions The study Introduction OK, but is it true for museums? Or is it still an unrealized possibility?

The Museum ecosystem on Twitter Conclusions The study Introduction > Questions we want to answer

The Museum ecosystem on Twitter > Questions we want to answer Conclusions The study Introduction The study is focused to offer insights over questions such as:

The Museum ecosystem on Twitter > Questions we want to answer The study Do the worldwide museums form a community on Twitter? Or several different communities? And then: which is the main criterion that explains the community structure: topic, language or country? Conclusions ·· ·· ·· Introduction The study is focused to offer insights over questions such as:

The Museum ecosystem on Twitter > Questions we want to answer The study ·· ·· ·· Do the worldwide museums form a community on Twitter? Or several different communities? And then: which is the main criterion that explains the community structure: topic, language or country? Do the Twitter communities seem to mimic patterns of offline relationships? Which are the communities? Which are the key players in each community? Does the small world principle apply? Conclusions ·· ·· ·· Introduction The study is focused to offer insights over questions such as:

The Museum ecosystem on Twitter > Questions we want to answer The study ·· ·· ·· ·· ·· Do the worldwide museums form a community on Twitter? Or several different communities? And then: which is the main criterion that explains the community structure: topic, language or country? Do the Twitter communities seem to mimic patterns of offline relationships? Which are the communities? Which are the key players in each community? Does the small world principle apply? And the strength of weak ties? To what extend? Which are the most influential museums, not in terms of followers, but in terms of influence within museums? Conclusions ·· ·· ·· Introduction The study is focused to offer insights over questions such as:

The Museum ecosystem on Twitter Conclusions The study Introduction > How?

The Museum ecosystem on Twitter > How? Conclusions The study Introduction We have analysed the Twitter talk among museums worldwide, using SNA (Social Network Analysis) techniques.

The Museum ecosystem on Twitter > How? ·· We are starting such a study with one Barcelona Museum. The study Later on we will focus on some case studies about the relationship of museums and their followers. This involves a much heavier use of the Twitter API. Conclusions ·· Introduction We have analysed the Twitter talk among museums worldwide, using SNA (Social Network Analysis) techniques.

The Museum ecosystem on Twitter > How? We have used the museum list from Museum Analytics*: Conclusions *museum-analytics.org Thank you to INTK team! The study Introduction 1.789 museums with a Twitter account

The Museum ecosystem on Twitter > How? The study * he final study will include data from a 12-month period. T Now we are showing results based on 9 months of data. Conclusions All their tweets from April 2013 123.972 interactions among museums 29.061 unique interactions Introduction And using the Twitter API we have got:

The Museum ecosystem on Twitter Communities UK Italy Spain The study The big picture The core graph Country/language UK Key role Introduction The study Conclusions 2

The Museum ecosystem on Twitter Conclusions The study Introduction > The big picture

Conclusions The study Introduction The Museum ecosystem on Twitter

Conclusions > The core graph The study Introduction The Museum ecosystem on Twitter

The study > The core graph Conclusions These are the 400 most relevant museums (relating to their importance in the graph –i.e. in the Twitter talk among museums) Introduction The Museum ecosystem on Twitter

The Museum ecosystem on Twitter Netherlands USA Germany United Kingdom Spain Conclusions >  ountry is C the key factor for explaining the graph structure Mexico The study Introduction France

The Museum ecosystem on Twitter Netherlands USA Germany There’s a clear country grouping in the interactions between the museums. The study Mexico Spain Conclusions >  ountry is C the key factor for explaining the graph structure Introduction Apart from the labeled countries there are important clusters for Canada, Australia and New Zealand placed France between USA and UK. And a Swedish one placed roughly between Netherlands, Germany and France. United Kingdom

The study >  K museums U have a Key role Conclusions Several UK museums are key players in the spread of information between Continental Europe ad USA museums. Introduction The Museum ecosystem on Twitter

United states 28,3% Unknown 18,24% United Kingdom 10,69% Netherlands 10,06% Germany 9,43% Spain 7,55% France 5,03% Mexico 4,4% Canada 2,52% Australia 1,89% Austria 0,63% Italy 0,63% New Zealand 0,63% Conclusions >  ommunities, countries C and some key players The study Introduction The Museum ecosystem on Twitter

The Museum ecosystem on Twitter Mexico 4,4% Canada 2,52% Australia 1,89% Austria 0,63% Italy 0,63% New Zealand 0,63% The study United states 28,3% Unknown 18,24% United Kingdom 10,69% Netherlands 10,06% Germany 9,43% Spain 7,55% France 5,03% Conclusions >  ommunities, countries C and some key players Introduction Community structure is almost the same as country grouping: Twitter relationships mimic offline relationships. We are not getting the most out of Twitter.

The Museum ecosystem on Twitter US community is the biggest, but UK museums have a central position. Speaking the world language is a clear advantage. 4 key US players: @museummodernart, @metmuseum, @guggenheim, @gettymuseum Mexico 4,4% Canada 2,52% Australia 1,89% Austria 0,63% Italy 0,63% New Zealand 0,63% The study United states 28,3% Unknown 18,24% United Kingdom 10,69% Netherlands 10,06% Germany 9,43% Spain 7,55% France 5,03% Conclusions >  ommunities, countries C and some key players Introduction 3 key British players: @britishmuseum, @sciencemuseum, @v_and_a

The Museum ecosystem on Twitter No Italian community, just a couple of scattered points. Mexico 4,4% Canada 2,52% Australia 1,89% Austria 0,63% Italy 0,63% New Zealand 0,63% The study United states 28,3% Unknown 18,24% United Kingdom 10,69% Netherlands 10,06% Germany 9,43% Spain 7,55% France 5,03% Conclusions >  ommunities, countries C and some key players Introduction The order of European countries does not seem to reflect the number of their “offline” museum visitors: UK, Netherlands, Germany, Spain, France, Italy.

London 76,98% None 11,11% Edinburgh 5,56% Casablanca 3,97% Amsterdam 1,59% Pacific Time (US & Canada) 0,79% Conclusions >  ountry communities 1: C UK The study Introduction The Museum ecosystem on Twitter

The Museum ecosystem on Twitter The study London 76,98% None 11,11% Edinburgh 5,56% Casablanca 3,97% Amsterdam 1,59% Pacific Time (US & Canada) 0,79% Conclusions >  ountry communities 1: C UK Introduction The Scottish cluster on the top. Another example of offline relationships replicated in the online environment.

Conclusions > Italy The study Introduction The Museum ecosystem on Twitter

The Museum ecosystem on Twitter The study > Italy Conclusions There are some isolated points: Italian museums unrelated to other Italian. Introduction We have gathered the Italian museums from the whole graph. Most of them are out of the core graph.

The Museum ecosystem on Twitter Language Conclusions > Spain The study Introduction Modularity

The Museum ecosystem on Twitter Language Even inside the Spanish group, the structure reflects the main language used by different museums on Twitter: Spanish, Catalan, and English. Conclusions > Spain The study Introduction Modularity

The Museum ecosystem on Twitter The study Conclusions How can this study help your museum? #MTF2014 at Twitter Introduction Conclusions Conclusions 3

The Museum ecosystem on Twitter > Conclusions The study Conclusions Most museums are not profiting the opportunities Twitter offer. Introduction ››3.500 museums at museum-analytic.org ››1.800 museums at Twitter ››400/500 museums really engaged with other museums

The Museum ecosystem on Twitter > Conclusions The study Conclusions 1.  ut there is a significant flow of information. (Small world principles applies) B Country is the main factor for explaining community structure 2. Not language: US and UK form different communities, so do Spain and Mexico 3.  nd not topic: there is not an archaeological museums community, or a contemporary art A community… That would have reflected a maturity in Twitter use. Introduction There is not a worldwide Twitter community, not even among those 400/500 museums.

The Museum ecosystem on Twitter > Conclusions The study Conclusions (Structural holes) Introduction There is a small set of key players in the spread of information and in the relationship among museums worldwide

The Museum ecosystem on Twitter Conclusions The study Introduction > How can this study help your museum?

The Museum ecosystem on Twitter > How can this study help your museum? ··  etect key players, analyse how they work on Twitter, D relate to them. The study Conclusions ··  onnecting the main component with your local or C topic-based community can be the first step. Be bilingual! (at least). Introduction ··  ecame a key player in your area (country, region, topic), B then go bigger.

The Museum ecosystem on Twitter > How can this study help your museum? The study Conclusions ··  tay tuned for the final paper, with more detailed graphics, S museum lists, etc. Introduction ··  se SNA approach to improve your work at Twitter, U your communication campaigns and the relationship with your followers.

The Museum ecosystem on Twitter Conclusions The study Introduction > #MTF2014 at Twitter

>  MTF2014 at Twitter # Conclusions The study Introduction The Museum ecosystem on Twitter

>  MTF2014 at Twitter # The study Conclusions We will write a post next week about the hashtag #mwf2014: who has used it, the mention and RT map about the conference, etc. Introduction The Museum ecosystem on Twitter

The Museum ecosystem on Twitter Thanks! The study Conclusions We want to partner with a museum for working a case study analysing the relationship with its Twitter followers. Are you interested? Contact us. Introduction For asking the final paper (April) contact us at: alex@lamagnetica.com @lamagnetica

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