Spot The Future: using network analysis to augment an online ethnography study

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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.

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Spot The Future: using network analysis to augment an online ethnography study

  1. 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. 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. 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. 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. 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. ! STF participants by country
  6. 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. ! ! ! ! Geocoding of STF participants by country (partial)
  7. 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. 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. 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. 10. E D G E RY D E R S L B G ! 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 ! 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 This work is property of UNDP and licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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