Fostering Friendships - Enhancing Social Bonds in the Classroom
COBWEB - The Academy of Finland research project
1. The Academy of Finland
Research Project
”COBWEB”
Academy of Finland ICT 2023-programme
Cross-disciplinary project with wide
international collaboration network
13. Workshop schedule and objectives
9:00
• Welcome (Hannu Kärkkäinen)
• Scenario of knowledge work (Thomas Olsson)
9:10 • Brief introduction of participants (round-the-table)
9:25
• Overview of Academy of Finland “Cobweb” project (PI’s of Cobweb)
• Preliminary schedule of Cobweb experiments (Ossi Nykänen)
10:00 • Break
10:15
• Workshop: Identification of knowledge work –related challenges and
development needs in partnering organizations of Cobweb (Facilitated by
Thomas Olsson)
11:45
• Wrap-up and next steps
12:00 • Lunch (1st floor of KampusAreena, Taco House)
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14. What if… we were able to work in new ways
in below manners / manners indicated in
described scenarios?
• Conference tinder / Researcher tinder
• Slush / Start-up matchmaking
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15. Cobweb goals
• The overall goal of our research is to support novel
ways of collaboration in and between professional
organizations that focus on knowledge work and
innovations (e.g. universities, start-ups, and SMEs in the
ICT sector)
• The overall question that we aim to answer in Cobweb is:
“How to utilize the potential and latent weak ties in
social big data in order to enhance collaboration in
knowledge work?”
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16. Milgram (1967): six degrees of
separation, small-world networks
Granovetter (1973): weak ties are
a key source of competitive
advantage
Burt (1992): Structural holes
Newman (2001): researcher
networks are small-worlds
Pentland (2015): collaboration
structure is key predictor of
performance; weak ties are vital in
breaking echo chambers
How to facilitate the emergence of weak ties
to support knowledge work productivity and
innovation?
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17. The unique combination of main project partner
expertise and resources ( data sources and
networks)
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18. Ties
• Strong ties: Strong ties are
the ones that a person really
trust (e.g. family)
• Weak ties: Refers to weak
links which may be known
(e.g. acquaintances)
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19. Tie Strength Dimensions
Based on Granovetters Definition
Tie
Strength
Amount of
Time
Emotional
Intensity
Intimacy
Reciprocal
Services
Based on Newer Definitions
(Marsden,Krackhardt,Li,Luam,Gilbert etc.)
Tie
Strength
Amount of
Time
Emotional
Intensity
Intimacy
Reciprocal
Services
Structural
Variables
Emotional
Support
Social
Distance
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20. TLO: Knowledge work productivity and social
media- based collaboration
• Vision
– Lean and automated knowledge work and knowledge co-creation by
means of modern collaboration methods and tools
• Key people:
– Hannu Kärkkäinen (PI),
– Jari Jussila,
– Karan Menon,
– Jayesh Gupta (Henna Salonius)
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21. MAT: Computational
Analytics & Semantic
Modeling
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• Vision
– New socially-enabled systems and data no person can manage
– …Exploit modern methods for weak tie analysis & exploitation
• Domain modeling
– Apply logic-based semantic modeling with method-based perspectives
– Review computational methods
• Computational definition(s) for weak ties (etc.)
– Study definitions based on logic, SNA, and soft computing
– Validate with concrete data & use cases, iterate
• Scenario & proof of concept application(s) development
• Key people:
– Ossi Nykänen (PI),
– Jukka Huhtamäki
22. IHTE & Social Technologies
• ”Proactive technology that augments social skills”
– Persuasive: how to ”make it happen” w.r.t. potential ties?
– Initiation, facilitation, enrichment
– Socio-technical perspective: tech. as social actor
– Visualization and sensemaking of Big Social Data
– Proximity-based solutions
• Focus on new social opportunities
and experimentation with end-users
• Key people:
– Thomas Olsson (PI),
– Ekaterina Olshannikova,
– Susanna Paasovaara
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23. Project Roadmap (Iterative)
2016 2017
u Q1: Inception:
Understanding of the
intersection of the three
research areas
u Q2: Backend
solutions for gathering
and modeling Big Social
Data
u Q3: First proof of
concept applications;
planning of experiments
u Q4: Experiments
begin
u Q1: First field studies
u Q2: Generalization
of methods
u Q3: Synthesis
u Q4: Dissemination
and next steps
Publications: Scientific peer reviewed conf. & journal, articles in Finnish popular science
and expert magazines
Researcher mobility: CWI, New Jersey Institute of Technology, etc.
Open source publications: Selected tools and algorithms 23
25. Part [1/2] – 45 min
• What are the current problems?
– Who don't meet even though they should? Why?
– What hinders more effective collaboration?
• What works well?
– Which existing practices could be strengthened?
• What new opportunities are there?
• What work would benefit from better collaboration?
• What kind of new social encounters should happen?
First alone (15min) à in groups (15) à to board & share (15)
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26. Part [2/2] – 45 min
• What would be good combinations of people to collaborate?
– What makes a relevant match?
– How to identify that? What data is available?
• How to enhance spread and cross-pollination of ideas?
• How to create serendipitous encounters?
• Describe & sketch & create stories!
– who, where, when, why, what type of work, etc.
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27. To gain new perspectives…
Ask yourself questions
”How could we…”
– [emphasize the good]
– [remove the bad]
– [question an assumption]
– [analogy]
– [identify unexpected resources]
– [change the time perspective]
– [change context]
– [add superpowers]
– [think what a specific person would do]
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”… make taxi driving feel like racing?”
”… remove waiting in traffic?”
”… change the whole taxi business?”
”… make taxi rides as enjoyable as a visit to hair dresser?”
”… make passenger more engaged?”
”… make rides feel like the future?”
”… make underground taxis?”
”… make taxi rides feel superhuman?”
”… be more ‘yes we can’?”
28. ”Release the ideas” – 15 min
• Max 3 min / group
• What are your…
– …best ideas
– …most important concerns
– …most crucial needs
– …utopian vision of the future
– …
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29. Wrap-up
• Further steps and schedule
Contacts / PI’s:
hannu.karkkainen@tut.fi
040-8490228
ossi.nykanen@tut.fi
040-8490730
thomas.olsson@tut.fi
040-8490819
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