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Observation and Analysis of 
Social Machines 
Markus Luczak-Roesch 
Web and Internet Science Group 
University of Southampton 
@mluczak | mail@markus-luczak.de
On the market of data analysis methods 
we are the customer. 
Image source: http://mrg.bz/uzjgr8
Social Machines? 
• Understanding socio-technical 
systems at the interface of 
• their intended problem solving 
capabilities and 
• the social interaction they 
support. 
• Derive indicators for the 
success of Social Machines 
and their underpinning in 
system components. 
Image source: http://www.onnai.com/wp-content/uploads/2009/11/social_machine_mkl2.gif
Zooniverse
Two paths to science
Talk and Task participation 
Talk contributions 
Classifications
Participation patterns 
20 
18 
16 
14 
12 
10 
8 
6 
4 
2 
0 
Project 
A 
Participant X 
Part. Y 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
11 
12 
13 
14 
15 
16 
17 
18 
19 
20 
21 
22 
23 
24 
25 
26 
27 
28 
29 
30 
31 
Ac#ve 
users 
in 
% 
Month 
since 
registra#on 
Project 
B 
Project 
C
Ecosystem effects 
PH 
GZ 
SF 
NN 
CC 
SG 
SW 
PF 
AP
Linguistic change 
Project initial 10% most recent 10% 
PH transit, star, day, aph, 
look, one, planet, like, 
possibl, dip 
day, transit, httparchive. . . , 
possibl, star, kid, dip, look, 
planet, like 
SF like, look, fish, sea, 
scallop, thing, imag, right, 
star, left 
corallinealga, anemon, 
object, hermitcrab, bryozoan, 
stalkedtun, shrimp, left, 
cerianthid, sanddollar 
NN field, record, one, use, 
enter, get, work, can, 
specimen, button 
like, field, record, date, name, 
can, click, look, get, label
Linguistic change 
Project initial 10% most recent 10% 
PH transit, star, day, aph, 
look, one, planet, like, 
possibl, dip 
day, transit, httparchive. . . , 
possibl, star, kid, dip, look, 
planet, like 
SF like, look, fish, sea, 
scallop, thing, imag, right, 
star, left 
corallinealga, anemon, 
object, hermitcrab, bryozoan, 
stalkedtun, shrimp, left, 
cerianthid, sanddollar 
NN field, record, one, use, 
enter, get, work, can, 
specimen, button 
like, field, record, date, name, 
can, click, look, get, label
Coordination and annotation 
Microposts Science 
91% 
10 
8 
6 
4 
2 
0 
PH SG SW NN GZ CC PF SF AP WS PH SG SW NN GZ CC PF SF AP WS 
Help Chat 
10 
8 
6 
4 
2 
0 
PH SG SW NN GZ CC PF SF AP WS PH SG SW NN GZ CC PF SF AP WS 
Vocabulary shift Vocabulary shift
RE-TRACE INFORMATION FLOWS TO 
CAPTURE SOCIO-TECHNICAL 
PROBLEM SOLVING 
Image source: http://commons.wikimedia.org/wiki/File:Minard.png
Information flows in Citizen Science
Information flows in Citizen Science
Information flows in Citizen Science
Information flows in Citizen Science
Information flows in Citizen Science
Social Machine algorithms as 
cascades of information 
• They emerge. 
• They branch and merge. 
• They may be(come) undesired. 
• They die. 
M1 
M3 M2
FROM SYSTEM SNAPSHOTS TO 
LONGITUDINAL STUDIES 
A footer
Observing Wikipedia 
The growth in edits (x), discussions (y) and Wikipedians (bubble 
radius) of Wikiprojects based on their root project page
Wikipedia: Past, Present, Future 
Synergistic to the Web’s Growth, Wikipedia has evolved from a resource of ? 
documents, to data, and to people. ? 
? 
Wikipedia continues to enrol and mobilise people and technology. ? 
The evolution of Wikipedia is part of a complex and fluid? 
eco-system of social machines. 
Understanding Wikipedia involves studying it as a system in and of itself, ? 
and as an actor in the in the growing and re-configuring Web.
Interactions Beyond Wikipedia
• Flows of information 
and interactions are 
the traces of socio-technical 
problem 
solving 
• Social Machines 
require 
observational and 
longitudinal 
analysis 
Markus Luczak-Roesch 
mail@markus-luczak.de 
www.markus-luczak.de 
@mluczak

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Observation and Analysis of Social Machines

  • 1. Observation and Analysis of Social Machines Markus Luczak-Roesch Web and Internet Science Group University of Southampton @mluczak | mail@markus-luczak.de
  • 2. On the market of data analysis methods we are the customer. Image source: http://mrg.bz/uzjgr8
  • 3. Social Machines? • Understanding socio-technical systems at the interface of • their intended problem solving capabilities and • the social interaction they support. • Derive indicators for the success of Social Machines and their underpinning in system components. Image source: http://www.onnai.com/wp-content/uploads/2009/11/social_machine_mkl2.gif
  • 5. Two paths to science
  • 6. Talk and Task participation Talk contributions Classifications
  • 7. Participation patterns 20 18 16 14 12 10 8 6 4 2 0 Project A Participant X Part. Y 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Ac#ve users in % Month since registra#on Project B Project C
  • 8. Ecosystem effects PH GZ SF NN CC SG SW PF AP
  • 9. Linguistic change Project initial 10% most recent 10% PH transit, star, day, aph, look, one, planet, like, possibl, dip day, transit, httparchive. . . , possibl, star, kid, dip, look, planet, like SF like, look, fish, sea, scallop, thing, imag, right, star, left corallinealga, anemon, object, hermitcrab, bryozoan, stalkedtun, shrimp, left, cerianthid, sanddollar NN field, record, one, use, enter, get, work, can, specimen, button like, field, record, date, name, can, click, look, get, label
  • 10. Linguistic change Project initial 10% most recent 10% PH transit, star, day, aph, look, one, planet, like, possibl, dip day, transit, httparchive. . . , possibl, star, kid, dip, look, planet, like SF like, look, fish, sea, scallop, thing, imag, right, star, left corallinealga, anemon, object, hermitcrab, bryozoan, stalkedtun, shrimp, left, cerianthid, sanddollar NN field, record, one, use, enter, get, work, can, specimen, button like, field, record, date, name, can, click, look, get, label
  • 11. Coordination and annotation Microposts Science 91% 10 8 6 4 2 0 PH SG SW NN GZ CC PF SF AP WS PH SG SW NN GZ CC PF SF AP WS Help Chat 10 8 6 4 2 0 PH SG SW NN GZ CC PF SF AP WS PH SG SW NN GZ CC PF SF AP WS Vocabulary shift Vocabulary shift
  • 12. RE-TRACE INFORMATION FLOWS TO CAPTURE SOCIO-TECHNICAL PROBLEM SOLVING Image source: http://commons.wikimedia.org/wiki/File:Minard.png
  • 13. Information flows in Citizen Science
  • 14. Information flows in Citizen Science
  • 15. Information flows in Citizen Science
  • 16. Information flows in Citizen Science
  • 17. Information flows in Citizen Science
  • 18. Social Machine algorithms as cascades of information • They emerge. • They branch and merge. • They may be(come) undesired. • They die. M1 M3 M2
  • 19. FROM SYSTEM SNAPSHOTS TO LONGITUDINAL STUDIES A footer
  • 20. Observing Wikipedia The growth in edits (x), discussions (y) and Wikipedians (bubble radius) of Wikiprojects based on their root project page
  • 21. Wikipedia: Past, Present, Future Synergistic to the Web’s Growth, Wikipedia has evolved from a resource of ? documents, to data, and to people. ? ? Wikipedia continues to enrol and mobilise people and technology. ? The evolution of Wikipedia is part of a complex and fluid? eco-system of social machines. Understanding Wikipedia involves studying it as a system in and of itself, ? and as an actor in the in the growing and re-configuring Web.
  • 23. • Flows of information and interactions are the traces of socio-technical problem solving • Social Machines require observational and longitudinal analysis Markus Luczak-Roesch mail@markus-luczak.de www.markus-luczak.de @mluczak