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A project from the Social Media Research Foundation: http://www.smrfoundation.org
Picturing
political social
media discour...
About Me
Introductions
Marc A. Smith
Chief Social Scientist / Director
Social Media Research Foundation
marc@smrfoundation...
Crowds matter
http://www.flickr.com/photos/amycgx/3119640267/
Crowds in social media matter
Crowds in social media have a hidden structure
https://demo-3dg-viz.herokuapp.com/
http://www.bonkersworld.net/organizational-charts/
Kodak
Brownie
Snap-
Shot
Camera
The first
easy to use
point and shoot!
https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=54648
https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=46679
#pdf15 Twitter NodeXL SNA Map and Report for Thursday, 04 Ju...
NodeXL Ribbon in Excel
NodeXL in Excel
We envision hundreds of NodeXL data collectors around the world
collectively generating a free and open archive of social ...
https://nodexlgraphgallery.org/Pages/Default.aspx?search=data+open
Top 10 Vertices:
@mlsif
@civichall
@mitgc_cm
@stone_rik
@civicist
@juansvas
@tableteer
@jcstearns
@ppolitics
@marc_smith
#...
#pdf15 Twitter NodeXL SNA Map and Report for Thursday, 04 June 2015 at 12:41 UTC
Broadcast Hub
(stone_rik)
Broadcast Hub
(...
A DAY LATER
#pdf15 Twitter NodeXL SNA Map and Report for Thursday, 04 June 2015 at 21:18 UTC
https://nodexlgraphgallery.org/Pages/Grap...
#pdf15 Twitter NodeXL SNA Map and Report for Thursday, 04 June 2015 at 21:18 UTC
https://nodexlgraphgallery.org/Pages/Grap...
prague Twitter NodeXL SNA Map and Report for Thursday, 01 October 2015 at 09:04 UTC
Prague: https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=54651
https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=54643
MZemanOficialni OR "Miloš Zeman" OR PrezidentZeman Twitter N...
Hubs
https://flic.kr/p/4Z6GHv
https://flic.kr/p/etEmeR
Bridges
http://www.flickr.com/photos/storm-crypt/3047698741
https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=46163
Top 10 Vertices:
@niyiabiriblog
@niyiabiri
@codeforamerica
@...
World Wide Web
Social media must contain
one or more
social networks
Crowds in social media form networks
Social Media
(email, Facebook, Twitter,
YouTube, and more)
is all about
connections
from people
to people.
37
Patterns are
left
behind
38
There are many kinds of ties…. Send, Mention,
http://www.flickr.com/photos/stevendepolo/3254238329
Like, Link, Reply, Rate...
“Think Link”
Nodes & Edges
Is related to
A BIs related to
Is related to
“Think Link”
Nodes & Edges
Is related to
A BIs related to
Is related to
Vertex1 Vertex 2 “Edge”
Attribute
“Vertex1”
Attribute
“Vertex2”
Attribute
@UserName1 @UserName2 value value value
A networ...
NodeXL imports “edges” from social media data sources
http://techpresident.com/news/22538/cro
wd-photography-cyber-tahrir-square
http://foreignpolicy.com/2012/06/18/visu
alizin...
Social media network analysis
• Social media is inherently made of networks,
– which are created when people link and repl...
https://nodexlgraphgallery.org/Pages/Default.aspx?search=civic
http://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/
[Divided]
Polarized Crowds
[Unified]
Tight Crowd
[Fragmented]
Brand Clusters
[Clustered]
Community Clusters
[In-Hub & Spok...
http://www.pewresearch.org/fact-tank/2014/02/20/the-six-types-of-twitter-conversations/
[Divided]
Polarized Crowds
[Unified]
Tight Crowd
[Fragmented]
Brand Clusters
[Clustered]
Community Clusters
[In-Hub & Spok...
#My2K
Polarized
#CMgrChat
In-group / Community
Lumia
Brand / Public Topic
#FLOTUS
Bazaar
New York Times Article
Paul Krugman
Broadcast: Audience + Communities
Dell Listens/Dellcares
Support
New Book in
Progress!
Social Network Maps Reveal
Key influencers in any topic.
Sub-groups.
Bridges.
SNA questions for social media:
1. What does my topic network look like?
2. What does the topic I aspire to be look like?
...
[Divided]
Polarized Crowds
[Unified]
Tight Crowd
[Fragmented]
Brand Clusters
[Clustered]
Community Clusters
[In-Hub & Spok...
Examples of social network scholarship
Margarita M. Orozco
Doctoral Student, School of Journalism &
Mass Communication
Uni...
Examples of social network scholarship
Margrét Vilborg Bjarnadóttir
Robert H. Smith School of Business |
University of Mar...
Studying the Colombian Peace
Process in Twitter
• Analyzing perceptions of the
peace process in Colombian
public opinion i...
Katy Pearce (@katypearce)
Assistant Prof of Communication
Studies technology & inequality in
Armenia & Azerbaijan.
#Protes...
Take Back The Tech!
Reclaiming ICTs against Violence Against Women
• Launched in 2006 by the Association for Progressive C...
2012: Outside institutions,
a grassroots conversation
REACtION - Collective Action Networks between Online and Offline Int...
2013: Accessing institutions,
a more structured conversation
REACtION - Collective Action Networks between Online and Offl...
2014: Inside institutions,
a centralized conversation
REACtION - Collective Action Networks between Online and Offline Int...
Margrét Vilborg Bjarnadóttir
Robert H. Smith School of Business | University of Maryland
Data Scientist | Parliamentary Sp...
C. Scott
Dempwolf,
PhD
Research Assistant
Professor & Director
UMD - Morgan State
Center for Economic
Development
http://w...
Social Network Analysis for the humanities?
Social Network Analysis and Ancient History
Prof. Diane Harris Cline
Associate...
Applying the insights of
social networks to social media:
Your social media audience is smaller…
…than the audiences of
te...
Build a collection of mayors
• Map multiple topics
– Your brand and company names
– Your competitor brands and company nam...
Speak the language of the mayors
• Use NodeXL content analysis to identify each
users most salient:
– Words
– Word pairs
–...
Speak the language of the mayors
The “perfect” tweet:
.@Theirname #Theirhashtag News about your brand
using their words h...
Speak the language of the mayors
Some shapes are better than others:
• The value of Broadcast versus community
network!
• From community to brand!
• Suppor...
Three network phases of social media success
Phase 1: You get an audience Phase 2: Your audience gets an audience Phase 3:...
Some shapes are better than others
• Each shape reflects the kind of social activity
that generates it:
– Divided: Conflic...
[Divided]
Polarized Crowds
[Unified]
Tight Crowd
[Fragmented]
Brand Clusters
[Clustered]
Communities
[In-Hub & Spoke]
Broa...
Request your own network map and report
http://connectedaction.net
Monitor your topics with social network maps
• Identify the
– Key people
– Groups
– Top topics
• Locate your social media ...
What we want to do:
(Build the tools to) map the social web
• Move NodeXL to the web: (Node[NOT]XL)
– Node for Google Doc ...
How you can help
• Sponsor a feature
• Sponsor workshops
• Sponsor a student
• Schedule training
• Sponsor the foundation
...
20151001 charles university prague - marc smith - node xl-picturing political social media discourse networks - mapping th...
20151001 charles university prague - marc smith - node xl-picturing political social media discourse networks - mapping th...
20151001 charles university prague - marc smith - node xl-picturing political social media discourse networks - mapping th...
20151001 charles university prague - marc smith - node xl-picturing political social media discourse networks - mapping th...
20151001 charles university prague - marc smith - node xl-picturing political social media discourse networks - mapping th...
20151001 charles university prague - marc smith - node xl-picturing political social media discourse networks - mapping th...
20151001 charles university prague - marc smith - node xl-picturing political social media discourse networks - mapping th...
20151001 charles university prague - marc smith - node xl-picturing political social media discourse networks - mapping th...
20151001 charles university prague - marc smith - node xl-picturing political social media discourse networks - mapping th...
20151001 charles university prague - marc smith - node xl-picturing political social media discourse networks - mapping th...
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20151001 charles university prague - marc smith - node xl-picturing political social media discourse networks - mapping the shape of the virtual crowd

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Mapping social media networks - a talk in Prague at Charles University

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20151001 charles university prague - marc smith - node xl-picturing political social media discourse networks - mapping the shape of the virtual crowd

  1. 1. A project from the Social Media Research Foundation: http://www.smrfoundation.org Picturing political social media discourse networks - mapping the shape of the virtual crowd
  2. 2. About Me Introductions Marc A. Smith Chief Social Scientist / Director Social Media Research Foundation marc@smrfoundation.org http://www.smrfoundation.org http://www.codeplex.com/nodexl http://www.twitter.com/marc_smith http://www.linkedin.com/in/marcasmith http://www.slideshare.net/Marc_A_Smith http://www.flickr.com/photos/marc_smith http://www.facebook.com/marc.smith.sociologist
  3. 3. Crowds matter
  4. 4. http://www.flickr.com/photos/amycgx/3119640267/ Crowds in social media matter
  5. 5. Crowds in social media have a hidden structure
  6. 6. https://demo-3dg-viz.herokuapp.com/
  7. 7. http://www.bonkersworld.net/organizational-charts/
  8. 8. Kodak Brownie Snap- Shot Camera The first easy to use point and shoot!
  9. 9. https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=54648
  10. 10. https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=46679 #pdf15 Twitter NodeXL SNA Map and Report for Thursday, 04 June 2015 at 21:18 UTC
  11. 11. NodeXL Ribbon in Excel
  12. 12. NodeXL in Excel
  13. 13. We envision hundreds of NodeXL data collectors around the world collectively generating a free and open archive of social media network snapshots on a wide range of topics. http://msnbcmedia.msn.com/i/msnbc/Components/Photos/071012/071012_telescope_hmed_3p.jpg
  14. 14. https://nodexlgraphgallery.org/Pages/Default.aspx?search=data+open
  15. 15. Top 10 Vertices: @mlsif @civichall @mitgc_cm @stone_rik @civicist @juansvas @tableteer @jcstearns @ppolitics @marc_smith #pdf15 Twitter NodeXL SNA Map and Report for Thursday, 04 June 2015 at 12:41 UTC Top 10 Hashtags: #pdf15 #ian1 #asmsg #bzbooks #bynr #civictech #nyc #authors #t4us #aga3
  16. 16. #pdf15 Twitter NodeXL SNA Map and Report for Thursday, 04 June 2015 at 12:41 UTC Broadcast Hub (stone_rik) Broadcast Hub (CivicHall, mlsif) Broadcast Hub (mitgc_cm) Brand Cluster (Isolates)
  17. 17. A DAY LATER
  18. 18. #pdf15 Twitter NodeXL SNA Map and Report for Thursday, 04 June 2015 at 21:18 UTC https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=46679 Top 10 Vertices: @mitgc_cm @stone_rik @mlsif @jgilliam @dantebarry @deanna @slaughteram @jcstearns @civicist @Digiphile Top 10 Hashtags: #pdf15 #civictech #tiimr #blacklivesmatter #ian1 #asmsg #bzbooks #bynr #pitmad #scfinalsvote
  19. 19. #pdf15 Twitter NodeXL SNA Map and Report for Thursday, 04 June 2015 at 21:18 UTC https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=46679 Community Cluster Broadcast Hub (digiphile) Brand Cluster (Isolates) Community Cluster Broadcast Hub (mlsif)
  20. 20. prague Twitter NodeXL SNA Map and Report for Thursday, 01 October 2015 at 09:04 UTC
  21. 21. Prague: https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=54651
  22. 22. https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=54643 MZemanOficialni OR "Miloš Zeman" OR PrezidentZeman Twitter NodeXL SNA Map and Report
  23. 23. Hubs
  24. 24. https://flic.kr/p/4Z6GHv https://flic.kr/p/etEmeR
  25. 25. Bridges
  26. 26. http://www.flickr.com/photos/storm-crypt/3047698741
  27. 27. https://nodexlgraphgallery.org/Pages/Graph.aspx?graphID=46163 Top 10 Vertices: @niyiabiriblog @niyiabiri @codeforamerica @civichall @knightfdn @omidyarnetwork @betanyc @digiphile @elle_mccann @participatory Top 10 Hashtags: #civictech #opendata #opengov #latism #tictec #govtech #newurbanpractice #womenforward #gov20 #civichall civictech Twitter NodeXL SNA Map and Report for Tuesday, 26 May 2015 at 05:25 UTC
  28. 28. World Wide Web Social media must contain one or more social networks Crowds in social media form networks
  29. 29. Social Media (email, Facebook, Twitter, YouTube, and more) is all about connections from people to people. 37
  30. 30. Patterns are left behind 38
  31. 31. There are many kinds of ties…. Send, Mention, http://www.flickr.com/photos/stevendepolo/3254238329 Like, Link, Reply, Rate, Review, Favorite, Friend, Follow, Forward, Edit, Tag, Comment, Check-in…
  32. 32. “Think Link” Nodes & Edges Is related to A BIs related to Is related to
  33. 33. “Think Link” Nodes & Edges Is related to A BIs related to Is related to
  34. 34. Vertex1 Vertex 2 “Edge” Attribute “Vertex1” Attribute “Vertex2” Attribute @UserName1 @UserName2 value value value A network is born whenever two GUIDs are joined. Username Attributes @UserName1 Value, value Username Attributes @UserName2 Value, value A B
  35. 35. NodeXL imports “edges” from social media data sources
  36. 36. http://techpresident.com/news/22538/cro wd-photography-cyber-tahrir-square http://foreignpolicy.com/2012/06/18/visu alizing-the-war-on-women-debate/ http://www.pewinternet.org/2014/02/20/mapping-twitter-topic- networks-from-polarized-crowds-to-community-clusters/
  37. 37. Social media network analysis • Social media is inherently made of networks, – which are created when people link and reply. • Collections of connections have an emergent shape, – Some shapes are better than others. • Some people are located in strategic locations in these shapes, – Centrally located people are more influential than others.
  38. 38. https://nodexlgraphgallery.org/Pages/Default.aspx?search=civic
  39. 39. http://www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/
  40. 40. [Divided] Polarized Crowds [Unified] Tight Crowd [Fragmented] Brand Clusters [Clustered] Community Clusters [In-Hub & Spoke] Broadcast Network [Out-Hub & Spoke] Support Network 6 kinds of Twitter social media networks
  41. 41. http://www.pewresearch.org/fact-tank/2014/02/20/the-six-types-of-twitter-conversations/
  42. 42. [Divided] Polarized Crowds [Unified] Tight Crowd [Fragmented] Brand Clusters [Clustered] Community Clusters [In-Hub & Spoke] Broadcast Network [Out-Hub & Spoke] Support Network 6 kinds of Twitter social media networks
  43. 43. #My2K Polarized
  44. 44. #CMgrChat In-group / Community
  45. 45. Lumia Brand / Public Topic
  46. 46. #FLOTUS Bazaar
  47. 47. New York Times Article Paul Krugman Broadcast: Audience + Communities
  48. 48. Dell Listens/Dellcares Support
  49. 49. New Book in Progress!
  50. 50. Social Network Maps Reveal Key influencers in any topic. Sub-groups. Bridges.
  51. 51. SNA questions for social media: 1. What does my topic network look like? 2. What does the topic I aspire to be look like? 3. What is the difference between #1 and #2? 4. How does my map change as I intervene? What does #YourHashtag look like? Who is the mayor of #YourHashtag?
  52. 52. [Divided] Polarized Crowds [Unified] Tight Crowd [Fragmented] Brand Clusters [Clustered] Community Clusters [In-Hub & Spoke] Broadcast Network [Out-Hub & Spoke] Support Network 6 kinds of Twitter social media networks
  53. 53. Examples of social network scholarship Margarita M. Orozco Doctoral Student, School of Journalism & Mass Communication University of Wisconsin- Madison Katy Pearce (@katypearce) Assistant Prof of Communication Studies technology & inequality in Armenia & Azerbaijan. Elena Pavan, Ph.D. Post Doctoral Research Fellow Dipartimento di Sociologia e Ricerca Sociale Università di Trento via Verdi 26, 38122 Trento (Italy)
  54. 54. Examples of social network scholarship Margrét Vilborg Bjarnadóttir Robert H. Smith School of Business | University of Maryland Data Scientist | Parliamentary Special Investigation Commission Prof. Diane Harris Cline Associate Professor of History George Washington University C. Scott Dempwolf, PhD Research Assistant Professor & Director UMD - Morgan State Center for Economic Development
  55. 55. Studying the Colombian Peace Process in Twitter • Analyzing perceptions of the peace process in Colombian public opinion in Twitter. • It is important to know what are citizens thinking, perceptions, and concerns. • Q: who are the main actors in Twitter in favor and against the peace process who are leading sources of information about it? • Colombians are the world’s 15th top Twitter users. For this reason this social media constitutes an important source of information about public opinion. 10/1/2015 64 UNIVERSITY OF WISC ONSIN–MADISONMargarita M. Orozco Doctoral Student, School of Journalism & Mass Communication University of Wisconsin- Madison
  56. 56. Katy Pearce (@katypearce) Assistant Prof of Communication Studies technology & inequality in Armenia & Azerbaijan. #ProtestBaku Azerbaijan
  57. 57. Take Back The Tech! Reclaiming ICTs against Violence Against Women • Launched in 2006 by the Association for Progressive Communications Women Rights Program (APC WRP) • Runs yearly during the 16 days against Violence Against Women (VAW) • Website http://www.takebackthetech.net • “16 daily actions” to reclaim ICTs against VAW and a Tweetathon • Explored in the context of the project REACtION (http://www.reactionproject.info) in relation to the interplay between the “offline” advocacy strategy and the “online” Twitter networks over time • Findings: shifts in the advocacy strategy shift the network structure – moving from the outside to the online of the institutions (lobbying at the Commission on the Status of Women) led to a centralized Twitter network where organizational and institutional accounts play most central roles REACtION - Collective Action Networks between Online and Offline Interactions - http://www.reactionproject.info. Grant post-doc 2011 by the Provincia Autonoma di Trento (Italy) Elena Pavan, Ph.D. Post Doctoral Research Fellow Dipartimento di Sociologia e Ricerca Sociale Università di Trento via Verdi 26, 38122 Trento (Italy)
  58. 58. 2012: Outside institutions, a grassroots conversation REACtION - Collective Action Networks between Online and Offline Interactions - http://www.reactionproject.info. Grant post-doc 2011 by the Provincia Autonoma di Trento (Italy)
  59. 59. 2013: Accessing institutions, a more structured conversation REACtION - Collective Action Networks between Online and Offline Interactions - http://www.reactionproject.info. Grant post-doc 2011 by the Provincia Autonoma di Trento (Italy)
  60. 60. 2014: Inside institutions, a centralized conversation REACtION - Collective Action Networks between Online and Offline Interactions - http://www.reactionproject.info. Grant post-doc 2011 by the Provincia Autonoma di Trento (Italy)
  61. 61. Margrét Vilborg Bjarnadóttir Robert H. Smith School of Business | University of Maryland Data Scientist | Parliamentary Special Investigation Commission Data Driven Large Exposure Estimation: A Case Study of a Failed Banking System Co-authors: Sigríður Benediktsdóttir and Guðmundur Axel Hansen Supporting Publications: Margrét V. Bjarnadóttir and Gudmundur A. Hanssen. 2010. Cross-Ownership and Large Exposures; Analysis and Policy Recommendations. Report of the Special Investigation Commission, Volume 9. Sigridur Benediksdottir and Margrét V. Bjarnadóttir. “Large Exposure Estimation through Automatic Business Group Identification”. Proceedings to DSMM 2014.
  62. 62. C. Scott Dempwolf, PhD Research Assistant Professor & Director UMD - Morgan State Center for Economic Development http://www.terpconnect.umd.edu/~dempy/
  63. 63. Social Network Analysis for the humanities? Social Network Analysis and Ancient History Prof. Diane Harris Cline Associate Professor of History; Affiliated faculty member in Classical and Near Eastern Literatures and Civilizations. George Washington University 1. New framework for analysis 2. Data visualization allows new perspectives – less linear, more comprehensive
  64. 64. Applying the insights of social networks to social media: Your social media audience is smaller… …than the audiences of ten influential voices.
  65. 65. Build a collection of mayors • Map multiple topics – Your brand and company names – Your competitor brands and company names – The names of the activities or locations related to your products • Identify the top people in each topic • Follow these people – 30-50% of the time they follow you back • Re-tweet these people (if they did not follow you) • 30-50% of the time they follow you back
  66. 66. Speak the language of the mayors • Use NodeXL content analysis to identify each users most salient: – Words – Word pairs – URLs – #Hashtags • Mix the language of the Mayors with your brand’s messages.
  67. 67. Speak the language of the mayors The “perfect” tweet: .@Theirname #Theirhashtag News about your brand using their words http://your.site #Yourhashtag
  68. 68. Speak the language of the mayors
  69. 69. Some shapes are better than others: • The value of Broadcast versus community network! • From community to brand! • Support and why community can be a signal of failure!
  70. 70. Three network phases of social media success Phase 1: You get an audience Phase 2: Your audience gets an audience Phase 3: Audience becomes community
  71. 71. Some shapes are better than others • Each shape reflects the kind of social activity that generates it: – Divided: Conflict – Unified: In-group – Brand: Fragmentation – Community: Clustering – Broadcast: Hub and spoke (In) – Support: Hub and spoke (Out)
  72. 72. [Divided] Polarized Crowds [Unified] Tight Crowd [Fragmented] Brand Clusters [Clustered] Communities [In-Hub & Spoke] Broadcast Network [Out-Hub & Spoke] Support Network [Low probability] Find bridge users. Encourage shared material. [Low probability] Get message out to disconnected communities. [Possible transition] Draw in new participants. [Possible transition] Regularly create content. [Possible transition] Reply to multiple users. [Undesirable transition] Remove bridges, highlight divisions. [Low probability] Get message out to disconnected communities. [High probability] Draw in new participants. [Possible transition] Regularly create content. [Possible transition] Reply to multiple users. [Undesirable transition] Increase density of connections in two groups. [Low probability] Dramatically increase density of connections. [High probability] Increase retention, build connections. [Possible transition] Regularly create content. [Possible transition] Reply to multiple users. [Undesirable transition] Increase density of connections in two groups. [Low probability] Dramatically increase density of connections. [Undesirable transition] Increase population, reduce connections. [Possible transition] Regularly create content. [Possible transition] Reply to multiple users. [Undesirable transition] Increase density of connections in two groups. [Low probability] Dramatically increase density of connections. [Low probability] Get message out to disconnected communities. [Possible transition] Increase retention, build connections. [High probability] Increase reply rate, reply to multiple users. [Undesirable transition] Increase density of connections in two groups. [Low probability] Dramatically increase density of connections. [Possible transition] Get message out to disconnected communities. [High probability] Increase retention, build connections. [High probability] Increase publication of new content and regularly create content.
  73. 73. Request your own network map and report http://connectedaction.net
  74. 74. Monitor your topics with social network maps • Identify the – Key people – Groups – Top topics • Locate your social media accounts within the network
  75. 75. What we want to do: (Build the tools to) map the social web • Move NodeXL to the web: (Node[NOT]XL) – Node for Google Doc Spreadsheets? – WebGL Canvas? D3.JS? Sigma.JS • Connect to more data sources of interest: – RDF, MediaWikis, Gmail, NYT, Citation Networks • Solve hard network manipulation UI problems: – Modal transform, Time series, Automated layouts • Grow and maintain archives of social media network data sets for research use. • Improve network science education: – Workshops on social media network analysis – Live lectures and presentations – Videos and training materials
  76. 76. How you can help • Sponsor a feature • Sponsor workshops • Sponsor a student • Schedule training • Sponsor the foundation • Donate your money, code, computation, storage, bandwidth, data or employee’s time • Help promote the work of the Social Media Research Foundation

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