2. Design/Science of participation
(1) Science through (platforms for mediated communication)
TMSP
(2) Science on (social science contributions about fundamentals of
psychology/communication/collaboration/cooperation)
“Hubble telescope” of social science
WE NEED TO ADDRESS THE DESIGN OF DATA (FOR) SCIENCE ISSUE DIRECTLY
3. On (1) – TMSP via SMPs
Awareness
Conversation and content exchange good;
content storage, indexing and search poor
Content sharing
Malleable as well as stable content
Coordination
Long and short term
Collaborative production
Lightweight to complex
Longevity
Currently questionable….
5. On (2)- Sciences of the social
Data quality
descriptive/predictive; observed/understood;
local/universal; reactive/proactive; stand-
alone/replicated
Science quality
Data stability/longevity, TOS, content and
social responsibility
WE NEED TO ADDRESS THE DESIGN OF DATA (FOR) SCIENCE ISSUE DIRECTLY
Designers : Statisticians : Computer scientists : Data Scientists : Social scientists
6. Focus on (2)
Mike Loukides
http://radar.oreilly.com/2010/06/what-is-data-science.html
7. On Data Science
“What differentiates data science from statistics is that
data science is a holistic approach. We’re increasingly
finding data in the wild, and data scientists are involved
with gathering data, massaging it into a tractable form,
making it tell its story, and presenting that story to others.”
The first step of any data analysis project is “data
conditioning,” or getting data into a state where it’s
usable.
8. On Data Science
The most meaningful definition I’ve heard: “big data” is
when the size of the data itself becomes part of the
problem.
The need to define a schema in advance conflicts with
reality of multiple, unstructured data sources, in which
you may not know what’s important until after you’ve
analyzed the data.
9. On Data Science
Data scientists … come up with new ways to view the
problem, or to work with very broadly defined problems:
“here’s a lot of data, what can you make from it?”
The future belongs to the companies who figure out how
to collect and use data successfully.
…and the scientists?
26. Recording and Sharing
Documenting
Personal and Collective
Memory
Competition
Status
Affiliation
Group Membership
Learning
Emulating
Awareness
Near and Far
Curiosity/Voyeuris
m
34. Data longevity
“Like all Commons members, the other qualitative
measure we value highly is the sheer inventiveness of
Flickr members who engage with the photographs.
Currently, Cornell saves links to examples of reuse on
delicious (http://www.delicious.com) and displays them
as a feed on its website.
45. Design/Science of participation
(1) Science through (platforms for mediated
communication)
TMSP
(2) Science on (social science contributions about
fundamentals of collaboration/cooperation)
“Hubble telescope” of social science
46. Reflections on requirements
Stability – the existence of content in an accessible (and hopefully the same)
format over time
Science requires
Consistency: consistently re-code the same data in the same way over a period of
time
Reproducibility: the tendency for a group of coders to classify categories membership
in the same way
Accuracy: or the extent to which the classification of a text corresponds to a
standard or norm statistically.
Validity
correspondence of the categories to the conclusions, avoiding ambiguity and
addressing multiple possible classifications
Proof: trust in the inferential procedures and clarity of what level of implication is
allowed. i.e. do the conclusions follow from the data or are they explainable due
to some other phenomenon
Generalizability of results to a theory
Cross-setting comparative interventions
47. On (2)- Sciences of the social
Data quality
descriptive/predictive; observed/understood;
local/universal; reactive/proactive; stand-
alone/replicated
Science quality
Data stability/longevity, TOS, content and
social responsibility
WE NEED TO ADDRESS THE DESIGN OF DATA (FOR) SCIENCE ISSUE DIRECTLY
Designers : Statisticians : Computer scientists : Data Scientists : Social scientists
49. Acknowledgements
On dating: Elizabeth Goodman; on Flickr: Shyong (Tony)
Lam, on instrumentation and analysis: David Ayman
Shamma & M. Cameron Jones; on Flickr Commons:
George Oates
Flickr photographers: Marina Noordegraaf
(Verbeeldingskr8), Tim Jagenberg, Nicolas Nova
Editor's Notes
Define serious and casual daters Serious: Looking for a long term partner Casual: Looking for short-term or one-time encounters Industry assumptions: Division between “ serious ” and “ casual ” daters in terms of what they ’ d pay for and the effort they put in Interviews were semi-structured, asking people to talk about the experience of planning and going on dates after only communicating online. Focusing on the work of dating -- the management of schedules, choosing locations, dealing with unexpected delays in traffic, handling anxiety.
