Social Media Metrics for the Cultural Heritage Sector
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Social Media Metrics for the Cultural Heritage Sector Developing a Prototype ttp://www.leocaillard.com/
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Transcript of Social Media Metrics for the Cultural Heritage Sector
Social Media Metrics for the Cultural Heritage Sector Developing a Prototype
http://www.leocaillard.com/
Program (20-25 min.)
About the context of this research.
Approach and choices.
Demonstration of the prototype.
Lessons learned and example results.
Q&A (~10 min.).
“MuseumCompass”
2-year research project
Goal: To support museum professionals with using digital media.
How can museums use the possibilities, created by digital media?
What is the effect on the public?
How does this change the role and the image of a museum?
How can a museum justify digital media activities to sponsors and subsidizers?
Specifically for exhibition
Interaction with publicPresent collection
Attract new audience
‘Binding’ people
Specifically for exhibition
Interaction with publicDisclose collection
Attract new audience
‘Binding’ people
‘Adding social media to a boring exhibit, is a boring exhibit with social media.’Van Vliet (2011), based on Mintz (1998)
Specifically for exhibition
Interaction with publicDisclose collection
Attract new audience
‘Binding’ people
What do these activities actually bring?
Specifically for exhibition
Interaction with publicDisclose collection
Attract new audience
‘Binding’ people
Social media are digital by nature.So first let’s start measuring what’s going on!
‘Social Media Metrics’
Software that automatically collects and visualizes data on social media activities.
We want to know:
• What the current and historic activities of
Dutch museums on social media are;
• What the impact of these activities is;
(the reactions of ‘the public’)
• How museums relate to one another, regarding
social media activities.
http://wiki.kenburbary.com/ > 220 tools
‘social monitoring’
‘social data analytics’ ‘media dashboards’
Our approach: build our own tool
(prototype).
“Social Media Museum Monitor”
Why develop a tool ourselves?
• Experiment and customize to learn.
• Ability to collect and study raw data-sets.
(also recognized by other researchers, e.g. Bruns and Liang
(2012))
• We could not find a solution that fits our needs.
(and budget…)
Low-hanging fruit
• No need for cooperation of museums. (i.e. ‘authorization’ of museums at the social media
platforms)
• At this moment enough data to
experiment with.
Facebook (‘social networking’)
Twitter (‘micro blogging’)
Flickr (‘photo sharing’)
YouTube (‘video sharing’)
Foursquare (‘location sharing’)
Selection of platformson basis of type and popularity / maturity
Selection of data-elements
How? (technically)
• Use public API to request data (REST);
• Parse returned JSON (PHP);
• Put everything in database (MySQL);
• (Combine and interpret data)
• Present the data in tables (PHP/HTML/CSS), and
in graphs (Google Charts, JavaScript).
How far are
we?
• Collected historical data of Facebook, Twitter,
and Flickr.
• Collecting current data on a daily basis.
• Visualizations for Twitter and Facebook.
• Foursquare and YouTube will be added soon.
6 months, 1 programmer, ~ 12 hours a week
Demo.
Lessons learned and discussion.
Lesson learned:
Collecting a selection of data may turn out to be inefficient.Non-relational database is an alternative.
Lesson learned:
Tracking the complete course of, for instance, ‘likes’ or retweets is very difficult.
1 day, 3 days, week interval is our solution.
Lesson learned:
Rate-limits for data causes headaches!Buying data is an alternative, but very costly.
Lesson learned:
All the different accounts and account types also causes headaches!Especially Facebook: Profiles, pages, places, communities, groups, etc.
Lesson learned:
Collecting social media account-ID’s is difficult to automate.425 museums * 5 platforms = 2125 checks…so time-consuming…
Feedback of potential
users.• Meeting with Stedelijk Museum and
Amsterdam Museum about:
- Their experience with and view on
social media;
- The first version of our monitor;
- Combination of data-elements.
• Overall feedback: positive about our approach
for the monitor, but as it is now not more than
‘nice to know’ info.
Finally, some example results.
Example result:
July 2008, “Kasteel Heeswijk” was the first museum with a Twitter-account.Now, more than 35% of the museums have a Twitter-account.
Example result:
Michael Blair from the USA has the most Facebook ‘likes’ on Dutch museum pages.
Our next challenge:
Making deeper analyses, and provide meaning for museum-professionals!
Thank you for your attention.
What are your questions?
