Paper https://www.researchgate.net/publication/303838852_An_empirically_informed_taxonomy_for_the_Maker_Movement

1. An empirically informed
taxonomy for the Maker Movement
Chris&an Voigt (ZSI), Calkin Suero Montero(UEF),
Massimo Menichinelli (FabLab-BCN, AU)
Centre for Social Innova9on | Dr. Chris&an Voigt
3rd International Conference on
Internet Science INSCI 2016 –
September 12-14, Florence, Italy

2. Context:
Collec9ve Awareness Pla>orm
• The Maker Movement is -among many things - a way to
empower people to take ownership of designs and means of
produc7on.
• Ownership also means controlling value preferences
embedded within a product
• For example
– materials used,
– features provided,
– energy consumed,
– openly designed etc.
Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 2
What defines the
Maker Movement ?
Taxonomy
• comparability
• track changes
in meaning
• fostering
abstractions

3. Problem Statement & Approach
• Taxonomies are frequently ad hoc crea&ons, i.e
– unclear origins or theore&cal frameworks
– may lack empirical founda&ons
• Approach tested
– Can social media, google trends and access sta7s7cs
inform taxonomic structures? => explanatory usefullness
• Objec&ve
– Test tools, methods and risks (modera&ng effects)
Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 3

4. Taxonomy refinement
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voigt.cmc@gmail.com
An empirically informed taxonomy 4

5. 1ST STEP: SELECTORS
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voigt.cmc@gmail.com
An empirically informed taxonomy 5

6. Seeds
ü people: maker, hacker;
ü places: makerspaces, hackerspaces, fablabs;
ü ac9vi9es: DIY, 3d-prin&ng, making, hacking
maker_educa&on.
Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 6
13.Ratto, M.: Critical making: Conceptual and material studies in
technology and social life. The Information Society. 27, 252–260 (2011).
14.Anderson, C.: Makers: the new industrial revolution. NY (2012).
15.Dougherty, D.: The maker movement. innovations. 7, 11–14 (2012).
… used as hashtags, search terms
and wikipedia pages – ‘seed word’
concept.

7. 2ND STEP: SOCIAL MEDIA ANALYSIS
Co-Word Analysis
Wikipedia Sta&s&cs
Google Trends (Search, Co-Search)
Emo&onal Profiling
Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 7

8. Co-Word analysis in R
• download tweets
(specified by one or more hashtags, max 13.000, within last 7 days)
• create corpus (i.e. combina&on of several text files)
• clean text (only alphabe&c chars, no numbers or brackets, no URL links or
retweet– RT – or @names)
• create term matrix (word by word matrix => gets huge)
• remove sparse terms (i.e. very few combina&ons)
• plot top 20 or top 30 co-words
Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 8
needed <- c ("twitteR", "tm”, "ggplot2”)
sapply (needed, require)

9. 13,000 tweets with #3dprin9ng
Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 9
Risk #1: Short time span & high impact events

10. Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 10

11. Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 11
Wikipedia Access Sta9s9cs
Another example
for the impact of
external events ...

12. Timeline interpreta9ons
• 'hackerspace’ are declining aler 2013
• visits to 'maker_culture' page are increasing
• 2013: publica&on of Chris Anderson's
Makers: The New Industrial Revolu7on.
• 2011 cover story from the Economist
"Print me a Stradivarius"
• no clear idea for decline of DIY aler 2013
Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 12

13. Google Trending
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voigt.cmc@gmail.com
An empirically informed taxonomy 13
Risk #2: Reflecting semantics (3D printing being part of DIY)
Risk #3: Non-testable data generation

14. 3RD STEP:
DRAFT TAXONOMIC STRUCTURE
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voigt.cmc@gmail.com
An empirically informed taxonomy 14

15. People:
DraX Taxonomic Structure
... so far co-word analysis, seemed the most
comprehensible approach.
Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 15

16. Outlook
• integra&on of &me dimension, indica&ng
decreasing and increasing terms (e.g. Google
Trending)
• tes&ng of automated taxonomy buidling (e.g.
in an educa&onal context where taxonomies
maner to support the exchange of materials
and lesson plans)
Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 16

17. BACK-UP
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voigt.cmc@gmail.com
An empirically informed taxonomy 17

18. EMOTION ANALYSIS
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voigt.cmc@gmail.com
An empirically informed taxonomy 18

19. Posi9ve emo9ons
– Clear: 'Lots of great prac&cal &ps for crea&ng a
library makerspace' (Eagerness)
– Ambiguous: 'Huge thanks to Cargill Salt for
approving our grant for our Maker-space. You're
helping to foster crea&vity and
innova&on!' (Liking)
– False: 'Aleph objects opens new fulfilment center
in Australia, offers free shipping - 3dprint.com
' (Fulfillment)
Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 19

20. Nega9ve emo9ons
– Clear: 'thanks! I want to try... afraid I'll do most of
the work in the minimal maker-space &me we
have!' (Distress)
– Ambiguous: 'Worried about #makerspace
logis&cs? #fallcue is here to help! It's not just for
tech! ' (Distress)
– False: 'If kids can imagine it, they can build it!
Perfect for blas&ng away boredom
#makerspace' (Weariness)
Centre for Social Innova&on |
voigt.cmc@gmail.com
An empirically informed taxonomy 20
Risk #4: Unknown classification errors