#AMC2013 Participatory Social Impact Research

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#AMC2013 Participatory Social Impact Research

  1. 1. Georgia Bullen Field Operations Technologist georgia@opentechinstitute.or g Participatory Social Impact Research
  2. 2. Creating digital networks is mostly a social process.
  3. 3. Video, Audio, Graphics, Web, IT/Networking
  4. 4. Documentation: Collection Methods • If This Then That (IFTTT) http://ifttt.com – Whenever “#detroitfuture” is tweeted  Update Wordpress Blog w/tweet info • Open Source Twitter Archive Tool – Immortal nTwitter, nTwitter, CouchDB, NodeJS – Javascript Library for listening on the Twitter API* • https://github.com/horixon/immortal-ntwitter • https://github.com/horixon/ntwitter • http://couchdb.apache.org/ • http://nodejs.org/ *In Glossary
  5. 5. Research Question Who is the “#detroitfuture” community? How has it evolved over the course of the program? – When and how often were people tweeting? • How does this relate to the media trainings and program events? – Who’s tweeting? – What are they tweeting about? – Who’s tweeting to whom?
  6. 6. What does the data look like? • Username • Tweet • Retweets • Date & Time • Users Mentioned • Lots and lots of metadata…
  7. 7. Looking at Tweets Over Time • When and how often were people tweeting? • How does this relate to the media trainings and program events? • Counts of Tweets by Date -> Chart • Information about events & trainings
  8. 8. #detroitfuture social network • Who’s tweeting to whom? • ParticipantA ParticipantB, Count of Tweets • Gephi – http://gephi.org – Network Visualization Software, Open Source, Easy to use – Calculate edge (links) and node (participant) scores – Run an analysis for communities within the community
  9. 9. #detroitfuture oct 2012
  10. 10. #detroitfuture june 2013
  11. 11. Key Findings • Online & Offline organization • Allows us to ask Innovative questions • Agency and authority for participants • Evolution from training  issues
  12. 12. Future Research • Natural Language Sentiment Analysis • Add interactive time control into the network visualization • Demographics based on Twitter Bios
  13. 13. Challenges • Have to teach how to use twitter first • APIs/Webformats/etc – need assistance with more technical skill sets • Twitter API doesn’t get everything • Keeping the community engaged in using the hashtag • Hashtag is public and can be usurped
  14. 14. Philadelphia – KEYSPOTS Program
  15. 15. Research Question Did the partnership function well? What was the impact of the BTOP funding on the partnership organizations? – Did the organizations involved collaborate with each other? – Did the organizations involved collaborate with outside organizations?
  16. 16. Collaboration Weighting Model Within Grant: 1 External to Grants: 2 Between Grants: 3
  17. 17. Analysis Methodology • Data cleaning & Coding – Clean for text matching – Grant assignments and weighting – OrganizationA OrganizationB, Weight of Collaboration
  18. 18. Thank you! Contact info: Georgia Bullen Email: georgia@opentechinstitute.org Twitter: @georgiamoon
  19. 19. Glossary • API – Application Programming Interface; Basically a query tool for interacting with web systems
  20. 20. Resources • OTI: http://oti.newamerica.net • Detroit Future Program: http://detroitfuture.org • #detroitfuture on twitter: http://twitter.com/search?q=%23detroitfuture&src= hash • Gephi: http://gephi.org • VLOOKUP & Excel Functions: http://office.microsoft.com/en-us/excel- help/vlookup-HP005209335.aspx • Pivot Tables: http://office.microsoft.com/en- us/excel-help/pivottable-reports-101- HA001034632.aspx

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