Spot The Future attempts to foresee near-future changes in Armenia, Egypt and Georgia by focusing on changemakers at the edge of society. The main method used is online ethnography. In this report, we show how we use network analysis of the conversation to augment the ethnography with quantitative information. The project was run by Edgeryders for UNDP's Innovation Unit.

1. T H E S P O T T H E F U T U R E
C O N V E R S AT I O N N E T W O R K
H O R I Z O N S C A N N I N G I N A R M E N I A , E G Y P T A N D G E O R G I A
Alberto Cottica, Benjamin Renoust and Inga Popovaite
This version: 15 July 2014

2. A B O U T T H I S
D O C U M E N T
• Interaction with peers in the social innovation
space is conducive to new inspiration, new
patterns of behaviour and, ultimately,
innovation. By fostering new relationships between
its participants, Spot The Future adds value and
impact to the consultation exercise. But not all
patterns of interaction are healthy: some imply the
opposite risks of balkanisation and groupthink.
• This document looks at Spot The Future as a
network of relationships. A network is instantiated
by drawing the comments from the database of the
Edgeryders platforms. A connection (edge) is
formed from Anna to Bob when Anna comment’s
Bob’s content.

3. T H E S T R U C T U R E O F
R E L AT I O N S H I P S
• The STF network involves 128 participants,
with 161 STF-related posts and 910
comments giving rise to 384 relational
exchanges. This network can be thought of as
the system of highways along which information
about social innovation in Armenia, Egypt and
Georgia travels.
• There is little or no insularity, and everybody
is heard out. The conversation is almost
unique, with a giant component connecting 122
out of 128 participants. Centrality analysis shows
that Edgeryders moderators play a key role in
connecting the network.
The Spot The Future conversation network

4. D I V E R S I T Y V S .
F O C U S
• The data indicate a healthy conversation,
with a good balance between diversity and
focus. This shows from the way the STF
conversation network is embedded in the
broader Edgeryders network. The two are not
disconnected, yet the STF network is still
clearly visible as a more densely connected
community within the broader network.
• This structure shows that participants from
the existing Edgeryders community engage
in STF, boosting the conversation’s diversity;
but also that focus is maintained, given that the
STF conversation maintains structural cohesion.
Spot The Future (orange) within the Edgeryders conversation
network

5. A G L O B A L
C O N V E R S AT I O N
• Participants in Armenia, Egypt and Georgia
contribute the most content, but there is a
healthy international variety of
contributions. Participants in the three STF
countries invest about 40% of their interactions
in-country, and the remaining 60% interacting
with people in different countries (both other
STF countries or non-STF countries.
• Overall, we recorded participants from 22
countries.
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STF participants by country

6. W I T H I N - C O U N T RY V S .
A C R O S S - C O U N T R I E S
• Egypt is central in the interaction across
STF countries, with over 10 unique
relationships both with Armenia and with
Georgia. Armenian participants did not
interact as much with Georgian ones.
!
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Geocoding of STF participants by country (partial)

7. S E M A N T I C S
• Ethnographic coding was applied to 161
posts and 782 comments. Coding is a standard
ethnographic technique. It consists of reading all
contributions and assigning relevant keywords to
snippets of texts.
• Such coding can be used to add semantic
meaning to each individual connection in the
network. 243 tags in 6 categories were identified
as recurring all along the STF conversation.
• If the conversation network is similar to a system
of highways, semantic meaning can be thought
of as the traffic actually riding on those highways.
STF keywords tree

8. C O O P E R AT I O N : T H E
M A I N C O N C E R N
• “Cooperation” is the keyword carried by most
edges – almost 80 occurrences. Roughly one
contributions in 10 over the whole exercise is
about cooperation.
• The strong presence of the “stf-approach”
keyword reflects a strong awareness of the
community of the collective intelligence exercise
they are engaged in. This connotes a respectful,
non-exploitative approach to research.
!
STF keywords by occurrence

9. P R O J E C T S A S
S O L U T I O N S
• Two keywords “interact” when they are mentioned by two
participants across an exchange. The network of
interactions across keywords shows three main
components.
• To the northwest, one finds issues (like gender-sterotypes)
and methods (like offline-meetings, transparency and
protest). This indicates the community comparing
solutions and matching them to problems.
• To the northeast, one find places. This indicates across-
country comparison.
• To the southeast, one finds a clique of Georgian projects.
(like Tbilisi-makerspace).
• Participants are discussing projects in the context of
problem-solutions conversations, against a backdrop of
international comparisons.
STF keywords interaction network (partial)

10. E D G E RY D E R S L B G
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F I N D O U T M O R E AT H T T P : / /
C O M PA N Y. E D G E RY D E R S . E U
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O R W R I T E T O A L B E R T O @ E D G E RY D E R S . E U
C O N TA C T
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