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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Do Museums Worldwide form a true Community on Twitter? Museum Twitter ecosystem (Social Network Analysis).

  • 2. ___ Do Museums Worldwide form a true Community on Twitter? Some insights on the museum Twitter ecosystem through Social Network Analysis and Network Science. { {
  • 3. The Museum ecosystem on Twitter The study Why this study? Questions we want to answer Methodology Introduction Introduction Conclusions 1
  • 4. The Museum ecosystem on Twitter Conclusions The study Introduction > Why this study?
  • 5. 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:
  • 6. 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:
  • 7. 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:
  • 8. 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
  • 9. 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?
  • 10. The Museum ecosystem on Twitter Conclusions The study Introduction > Questions we want to answer
  • 11. 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:
  • 12. 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:
  • 13. 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:
  • 14. 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:
  • 15. The Museum ecosystem on Twitter Conclusions The study Introduction > How?
  • 16. 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.
  • 17. 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.
  • 18. 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
  • 19. 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:
  • 20. 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
  • 21. The Museum ecosystem on Twitter Conclusions The study Introduction The big picture
  • 23. Conclusions The core graph The study Introduction The Museum ecosystem on Twitter
  • 24. 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
  • 25. 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
  • 26. 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
  • 27. 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
  • 28. 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
  • 29. 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.
  • 30. 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
  • 31. 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.
  • 32. 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
  • 33. 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.
  • 34. Conclusions Italy The study Introduction The Museum ecosystem on Twitter
  • 35. 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.
  • 36. The Museum ecosystem on Twitter Language Conclusions Spain The study Introduction Modularity
  • 37. 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
  • 38. The Museum ecosystem on Twitter The study Conclusions How can this study help your museum? #MTF2014 at Twitter Introduction Conclusions Conclusions 3
  • 39. 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
  • 40. 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.
  • 41. 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
  • 42. The Museum ecosystem on Twitter Conclusions The study Introduction How can this study help your museum?
  • 43. 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.
  • 44. 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.
  • 45. The Museum ecosystem on Twitter Conclusions The study Introduction #MTF2014 at Twitter
  • 46. MTF2014 at Twitter # Conclusions The study Introduction The Museum ecosystem on Twitter
  • 47. 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
  • 48. 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: [email protected] @lamagnetica