Purpose and Risks

1. Data Visualisa*on
purpose & risks
4 risks
50,000 tweets
6 years of Google trends
Centre for Social Innova*on | Dr. Chris<an Voigt

2. Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 2
Risk #1:
Wie lang dauert die
Interpretation eines
Chorddiagramms ?
eine einfache Excel
Tabelle wäre event.
aussagekräftiger ...
Ästhe<k vs. Funk<on
Chord-Diagrams
of ≈ 100 projects

3. 1st Problem, 2nd Data,
3rd Visualisa*on
• Taxonomy Intro
• Tweets & Co-words
• Wikipedia Access Stats
• Google Trending Terms
• Google related searches,
• Emo<onal analysis
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 3

4. Bloom’s Taxonomy of
learning objec*ves
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 4

5. Problem statement
• Taxonomies are oQen ad hoc
• … may lack empirical founda<ons
(unclear origins)
• Approach tested:
Can social media, google trends and access
stats inform taxonomic structures?
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 5

6. 1st step: Selectors
ü people: maker, hacker;
ü places: makerspaces, hackerspaces, fablabs;
ü ac6vi6es: DIY, 3d-prin<ng, making, hacking,
maker_educa<on.
… used as hashtags, search terms and
wikipedia pages – ‘seed word’ concept.
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 6

7. 1st Taxonomic structures
… how did we get there?
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 7

8. CO-WORD ANALYSIS
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 8

9. 13,000 tweets with #3dprin*ng
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 9
Risk #2: short time span & high impact events

10. Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 10

11. Required Steps 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
• also possible – clustering of words (Ward; k-means) ?
• needed <- c ("twiheR", "tm”, "ggplot2”)
• sapply(needed, require)
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 11

12. WIKIPEDIA ACCESS STATS
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 12

13. Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 13

14. Some interpreta*ons
• 'hackerspace’ are declining aQer 2013
• visits to 'maker_culture' page are increasing
• 2013: publica<on of Chris Anderson's
Makers: The New Industrial Revolu6on.
• 2011 cover story from the Economist
"Print me a Stradivarius"
• no clear idea for decline of DIY aQer 2013
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 14

15. Required Steps in R
• Read access stats
• Plot diagram
• library (wikipediatrend)
• library (ggplot2)
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 15

16. GOOGLE TRENDING
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 16

17. Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 17
Risk #3: not specific enough

18. GOOGLE RELATED SEARCHES
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 18

19. Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 19
Risk #4: Non-testable data generation

20. EMOTION ANALYSIS – OUTLOOK
Centre for Social Innova<on |
C. Voigt
Data Viz & Taxonomies 20

21. Posi*ve emo*ons
– 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 |
C. Voigt
Data Viz & Taxonomies 21

22. Nega*ve emo*ons
– 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 |
C. Voigt
Data Viz & Taxonomies 22
Risk #4: Unknown classification errors