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Public Diplomacy for the Social Media Age

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#Diplometrics (Ottawa, Canada, April 21, 2016)

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Public Diplomacy for the Social Media Age

  1. 1. PUBLIC DIPLOMACY FOR THE SOCIAL MEDIAAGE ANATOLIYGRUZD (@GRUZD) Ottawa, Canada April 21, 2016 Canada Research Chair in Social Media Data Stewardship Associate Professor, Ted Rogers School of Management Director of the Social Media Lab Ryerson University
  2. 2. Social Media Lab (Ryerson University, Toronto, Canada) • Social Media Analytics • Social Media Data Stewardship • Measuring Influence on Social Media • Online Political Engagement • Learning Analytics • Social Media & Health
  3. 3. RESEARCH FUNDING & PARTNERS
  4. 4. #OccupyGezi Supporters in Victoria, BC From this… Photo credit: Anatoliy Gruzd In the Social Media Lab, we study how social media …. Anatoliy Gruzd How social media can support online communities, social activism & political engagement?
  5. 5. Photo credit: Karl Schönswetter … to this #OccupyGezi: Gezi Parki Protest, Turkey (2013) 5 In the Social Media Lab, we study how social media …. How social media can support online communities, social activism & political engagement?
  6. 6. Key Points 1. Social Media Data is a good proxy to study online and offline social interactions 2. Social Network Analysis is an effective method to analyze social media data 7@gruzd Anatoliy Gruzd
  7. 7. Outline • Background - SNA • Social Media Use during the 2014 EuroMaidan Revolution • Review of Social Media Platforms • VKontakte • Twitter • Current & Future Challenges in Social Media Analytics 8@gruzd Anatoliy Gruzd
  8. 8. 1.5B users 400M users 300M users Growth of Social Media Data @gruzd Anatoliy Gruzd 9
  9. 9. Decision Making in domains such as Politics, Health Care and Education @gruzd Anatoliy Gruzd 10 + More Ways to Access Social Media Data Public APIs Data Resellers Self- collected/ reported
  10. 10. Data -> Visualizations -> Understanding How to Make Sense of Social Media Data? Data and Visual Analytics @gruzd Anatoliy Gruzd 11
  11. 11. How to Make Sense of Social Media Data? Geo-based & Text Analytics @gruzd Anatoliy Gruzd 12
  12. 12. Common approach for collecting social network data: • Surveys or interviews Problems with surveys or interviews • Time-consuming • Questions can be too sensitive • Answers are subjective or incomplete • Participant can forget people and interactions • Different people perceive events and relationships differently How to Make Sense of Social Media Data? Social Network Analysis (SNA) @gruzd Anatoliy Gruzd 13
  13. 13. Studying Online Social Networks http://www.visualcomplexity.com/vc Forum networks Blog networks Friends’ networks (Facebook, Twitter, Google+, etc…) Networks of like-minded people (YouTube, Flickr, etc…) @gruzd Anatoliy Gruzd 14
  14. 14. 1) Represent data as a network Nodes = People Edges /Ties = Relations (ex. Who is a friend with whom, Who replies to whom, etc.) •2) Apply Social Network Analysis (SNA) Examining Social Media Data from a Network Perspective @gruzd 15Anatoliy Gruzd
  15. 15. Advantages of Using Social Network Analysis (SNA) Once the network is discovered, we can find out: • How do people interact with each other, • Who are the most/least active members of a group, • Who is influential in a group, • Who is susceptible to being influenced, etc… @gruzd 16Anatoliy Gruzd
  16. 16. SNA Measures Macro-level Density Diameter Reciprocity Modularity • Density indicates the overall connectivity in the network (the total number of connections divided by the total number of possible connections). • It is equal to 1 when everyone is connected to everyone. Anatoliy Gruzd 17@gruzd User1 User3 User2 Density = 1
  17. 17. SNA Measures Macro-level Density Diameter Reciprocity Modularity • Diameter gives a general idea of how “wide” the network is; the longest of the shortest paths between any two nodes in the network. Anatoliy Gruzd 18@gruzd #1 User1 User3 User2 User4 Diameter = 3 #2 #3
  18. 18. SNA Measures Macro-level Density Diameter Reciprocity Modularity • Reciprocity shows how many online participants are having two- way conversations. • In a scenario when everyone replies to everyone, the reciprocity value will be 1. Anatoliy Gruzd 19@gruzd User2 User1 User3 User4 Reciprocity=1
  19. 19. SNA Measures Macro-level Density Diameter Reciprocity Modularity • Modularity provides an estimate of whether a network consists of one coherent group of participants who are engaged in the same conversation and who are paying attention to each other (values closer to 0); • or whether a network consists of different conversations and communities with a weak overlap (values closer to 1). Anatoliy Gruzd 20@gruzd
  20. 20. Outline • Background • Social Media Use during the 2014 EuroMaidan Revolution • Review of Social Media Platforms • VKontakte • Twitter • Current & Future Challenges in Social Media Analytics 21@gruzd Anatoliy Gruzd
  21. 21. Today’s focus: 2014 EuroMaidan Revolution | Revolution of Dignity 22 "2014-02-21 11-04 Euromaidan in Kiev" by Amakuha. Licensed under CC BY-SA 3.0 via Wikimedia @gruzd Anatoliy Gruzd
  22. 22. Social Media Use during the 2014 EuroMaidan Revolution Summary of the Case Study • First “Social Media” Revolution in Ukraine • 2004 “Orange Revolution” (Pre-social media) • Internet penetration in Ukraine ~12% (Lysenko & Desouza, 2010) • Facebook was founded in 2004, Youtube-2005, Twitter-2006, Instagram-2010 • Use of multiple social media platforms • Prior social media “revolutions” primarily focused on a single platform: Facebook revolution in Tunisia (2010/2011); Twitter revolution in Iran (2009/2010) • Content is often duplicated across multiple platforms • Social media used by both Pro & Anti-Maidan activists • Pro-Western (Maidan) vs Pro-Russian groups (Anti- Maidan) • Social media use by news agencies, activist groups, governments, elective officials and politicians • Social media use for “locals” vs. for Westerners (in English) 23@gruzd Anatoliy Gruzd
  23. 23. Background: 2014 EuroMaidan Revolution | Revolution of Dignity 24 "2014-02-21 11-04 Euromaidan in Kiev" by Amakuha. Licensed under CC BY-SA 3.0 via Wikimedia November 21, 2013 - Ukraine gov. suspended the trade & association agreement with EU @gruzd Anatoliy Gruzd
  24. 24. February 18-19, 2014: Protests in Kyiv (capital) Turned Deadly 25 source: http://liveuamap.com RUSSIA UKRAINE @gruzd Anatoliy Gruzd
  25. 25. February 18-19, 2014: Protests in Kyiv Turned Deadly 26 "Barricade line separating interior troops and protesters. Clashes in Kyiv, Ukraine. Events of February 18, 2014-2" by Mstyslav Chernov/Unframe/http://www.unframe.com/ - Licensed under CC BY-SA 3.0 via Wikimedia Commons @gruzd Anatoliy Gruzd
  26. 26. February 18-19, 2014: Protests in Kyiv Turned Deadly 27 "Euromaidan in Kiev 2014-02-19 12-06" by Amakuha. Licensed under CC BY-SA 3.0 via Wikimedia Commons @gruzd Anatoliy Gruzd
  27. 27. February-March, 2014: Pro & Anti-Maidan Protests SpreadAcross Ukraine 28 source: http://liveuamap.com @gruzd Anatoliy Gruzd
  28. 28. February-April 2014:Awave of Anti-Maidan protests in South-East 29@gruzd Photo credit: Andriy Makukha. Licensed under CC BY-SA 3.0 via Wikimedia Commons Anatoliy Gruzd
  29. 29. March 2014: Annexation of Crimea by Russia 30 source: http://liveuamap.com @gruzd Anatoliy Gruzd
  30. 30. April 2014:Anti-Terrorist Operation (ATO) against pro-Russian Self-proclaimed republics: Donetsk People’s Republic (DPR) & Lugansk People’s Republic (LPR) 31 source: http://liveuamap.com @gruzd Anatoliy Gruzd
  31. 31. Outline • Background • Social Media Use during the 2014 EuroMaidan Revolution • Review of Social Media Platforms • VKontakte • Twitter • Current & Future Challenges in Social Media Analytics 32@gruzd Anatoliy Gruzd
  32. 32. Review of Social Media Platforms: Websites – still important, linking to social media accounts http://euromaidansos.org/ 33@gruzd Anatoliy Gruzd
  33. 33. Review of Social Media Platforms: Blogs http://fakecontrol.org/blog/2014/03/04/george-bush/ 34@gruzd Anatoliy Gruzd
  34. 34. Review of Social Media Platforms Youtube & ustream.tv:Activists, News agencies, Gov.officials https://www.youtube.com/watch?v=I_cNDGU7k98 http://www.ustream.tv/recorded/44404145 35@gruzd Anatoliy Gruzd Future unrests: Twitter's Periscope?
  35. 35. Review of Social Media Platforms Instagram: Photo Sharing during Rallies 36 http://www.the-everyday.net @gruzd Anatoliy Gruzd
  36. 36. Review of Social Media Platforms Wikipedia: Editors’ Debate about the Status of Crimea 37@gruzd Anatoliy Gruzd
  37. 37. Review of Social Media Platforms Facebook Groups & Pages: Activists https://www.facebook.com/groups/223479324489867 https://www.facebook.com/EvromaidanSOS 38@gruzd Anatoliy Gruzd
  38. 38. Outline • Background • Social Media Use during the 2014 EuroMaidan Revolution • Review of Social Media Platforms • VKontakte • Twitter • Current & Future Challenges in Social Media Analytics 39@gruzd Anatoliy Gruzd
  39. 39. This part is based on our recent papers on VK groups Gruzd, A. & Tsyganova, K. (2015). Information Wars and Online Activism During the 2013/2014 Crisis in Ukraine: Examining the Social Structures of Pro- and Anti-Maidan Groups. Policy & Internet 7(2). DOI: 10.1002/poi3.91 40@gruzd Anatoliy Gruzd Acknowledgments • We thank Emad Khazraee, Dmitri Tsyganov, Andrea Kampen, Philip Mai, and Elizabeth Dubois for their help on this project.
  40. 40. About Vkontakte – #1 Social Networking Website in Ukraine 41 source: http://en.wikipedia.org @gruzd Anatoliy Gruzd
  41. 41. Example: VK Group User Interface – Posts, Likes, Comments… 42@gruzd Anatoliy Gruzd
  42. 42. Example: VK Group User Interface – Discussion board, Links & Media Files… 43@gruzd Anatoliy Gruzd
  43. 43. Pro-Maidan (pro-Western) &Anti-Maidan (pro-Russian) Groups on VK ~Over 3,500 groups with membership from 100K+ to under 10 members 44 Anti-Maidan groupPro-Maidan group @gruzd Anatoliy Gruzd
  44. 44. 1) Represent data as a network Nodes = People Edges /Ties = Relations (ex. Who is a friend with whom, Who replies to whom, etc.) •2) Apply Social Network Analysis (SNA) We Study Online Groups from a Network Perspective @gruzd 45Anatoliy Gruzd
  45. 45. Different Friends’ Networks: What can we learn from them? 46 Anti-Maidan groupPro-Maidan group @gruzd Anatoliy Gruzd
  46. 46. Different Friends’ Networks: What can we learn from them? 47 Anti-Maidan groupPro-Maidan group @gruzd Anatoliy Gruzd
  47. 47. Data Collection 48 PRO1 PRO2 ANTI1 ANTI2 Num. of Nodes 141,542 96,402 60,506 69,029 Num. of Connections 338,344 221,452 280,678 192,273 • Used VK Public API • Communities – information about groups and group members • Wall – posts and comments • Likes – “likes” that members and visitors leave on posts • Friends – group members’ friendship relations • Data collection: 2 most popular public Pro-Maidan and Anti-Maidan groups • Period: February 18 – May 25, 2015 @gruzd Anatoliy Gruzd
  48. 48. Method 49 • Social Network Analysis • SNA measures (e.g., centrality, density, network diameter) • Exponential Random Graph Modeling (ERGM) – test association tendencies • Walktrap Community Detection algorithm - identify and describe highly connected subgroups • Network Visualization using LGL (Large Graph Layout) • Manual Content Analysis of • Group pages and posts • Sample of public user profiles • Research software • Package R (libraries statnet and igraph) • Tableau for visual analytics @gruzd Anatoliy Gruzd
  49. 49. • Formed in early April 2014 to support Maidan and Antiterrorist Operation (ATO) Yellow – users from Ukraine; Red – from Russia; Green – other countries; The layout algorithm is LGL (Large Graph Layout). Isolated nodes are not visible. 50@gruzd Anatoliy Gruzd VK Group Example – Pro Maidan #1 (Pro-Western) Friends’Network (>140k members)
  50. 50. Avg#ofFriendsAvg#ofLikes Subgroup 3 Subgroup 42 Crimean Tatars Spam (Marketing) “Walktrap” Community Detection Example: VK Group – Pro-Maidan @gruzdAnatoliy Gruzd 51
  51. 51. Subgroup 3 Anatoliy Gruzd Example: VK Group – Pro-Maidan Spam (Marketing) % of spammers among participants with friends is higher than among all group members Spam accounts 5% Spam accounts 15% Group members Members w/friends @gruzd 52
  52. 52. VK Group Example –Anti-Maidan #2 (Pro-Russian) Friends’Network (69K members) One densely connected cluster - suggesting a stronger agreement among group members from both Ukraine and Russia • In existence since 2011, focused on Anti- American & Pro-Russia discussions. • Since the events on Maidan in early 2014, shifted its focus to support Anti-Maidan activism & the two self-proclaimed republics – Donetsk and Lugansk People's Republics. 53@gruzd Anatoliy Gruzd
  53. 53. VK Group Example –Anti-Maidan #2 Friends’Network (69K members) Politically active accounts 54@gruzd Anatoliy Gruzd Avg#ofFriendsAvg#ofLikes
  54. 54. Conclusions - Comparing Groups across Political Divide PRO1 ANTI2 Number of Nodes 141,542 69,029 Number of Connections 338,344 192,273 Modularity Index 0.58 0.24 55@gruzd Anatoliy Gruzd • Modularity provides an estimate of whether a network consists of one coherent group of participants (values closer to 0); • or whether a network consists of different conversations and communities with a weak overlap (values closer to 1).
  55. 55. VKontakte Conclusions - Geography Matters! • Although all four groups included people from both Ukraine and Russia, the ERGM models confirmed the tendency of group members to friend others in the same country. • Furthermore, we also observed homophily among users from the same city for the top-10 cities with the most number of VK users in all groups 56 Online social networks likely represent local and potentially pre-existing social networks "Euromaidan Protests" by Lvivske, NickK - Sources for particular cities are given at w:uk:Євромайдан у регіонах України. Licensed under CC BY-SA 3.0 via Wikimedia Commons @gruzd Anatoliy Gruzd
  56. 56. VKontakte Conclusions - Position of Spam & Marketing Accounts • Spam & marketing accounts appeared to be organized in a densely connected subgroup with high degree centrality values and low user engagement • It is important to differentiate spam & marketing accounts from group supporters who might also be located in smaller, somewhat isolated subgroups because of their minority status in the group (e.g., Crimean Tatars) • Interestingly, this pattern was not observed in the ANTI1 or ANTI2 groups. 57@gruzd Anatoliy Gruzd
  57. 57. Outline • Background • Social Media Use during the 2014 EuroMaidan Revolution • Review of Social Media Platforms • VKontakte • Twitter • Current & Future Challenges in Social Media Analytics 58@gruzd Anatoliy Gruzd
  58. 58. This part is based on a forthcoming chapter on Research Methods Gruzd, A., Mai, P., Kampen, A. (2016). A how-to for using Netlytic to collect and analyze social media data: A case study of the use of Twitter during the 2014 Euromaidan Revolution in Ukraine. The SAGE Handbook of Social Media Research Methods. 59@gruzd Anatoliy Gruzd
  59. 59. Automated Discovery of Social Networks Twitter Data Examples Network Tie @MarcosCarvo -> @prefeiturasl @gruzd Anatoliy Gruzd 60 Network Tie @Gruzd -> @SidneyEve Connection type: Mention Connection type: Reply
  60. 60. @John @Peter @Paul • Nodes = People • Ties = “Who retweeted/ replied/mentioned whom” • Tie strength = The number of retweets, replies or mentions Automated Discovery of Social Networks Twitter Networks @gruzd Anatoliy Gruzd 61
  61. 61. Source: Twitter Search API Request Rate: Hourly, up to 1000 tweets Time frame: Feb 18, 2014 – March 14, 2014 Tweeting about Ukraine in 3 languages Україна Украина Ukraine Presumed Language Ukrainian Russian English # Tweets 200,956 527,112 591,394 # Unique Users 46,641 141,541 246,113 @gruzd Anatoliy Gruzd 62
  62. 62. Twitter Communication Network # Tweets 200,956 # Unique Users 46,641
  63. 63. Twitter Communication Network Top 10 Mentioned Users (activists, news, politicians) Jared Leto expressed support of Ukrainian people in his Oscars award acceptance speech
  64. 64. Twitter Communication Network # Tweets 527,112 # Unique Users 141,541
  65. 65. Twitter Communication Network Top 10 Mentioned Users (mostly Russian news agencies & journalists)
  66. 66. # Tweets 591,394 # Unique Users 246,113
  67. 67. Top 10 Mentioned Users (mostly news accounts)
  68. 68. Topics over Time in Tweets that mentioned “Ukraine” @gruzd Anatoliy Gruzd 73
  69. 69. Cross Network Comparison @gruzd Anatoliy Gruzd 74 Україна (in Ukrainian) Украина (in Russian) Ukriane (in English)
  70. 70. Україна (in Ukrainian) Украина (in Russian) Ukraine (in English) Nodes 3223 17964 29647 Edges 3160 21107 27854 Density 0.000304 0.000065 0.000031 Diameter 29 39 61 Reciprocity 0.026 0.057 0.029 Modularity 0.85 0.78 0.89 Anatoliy Gruzd 75@gruzd Cross Network Comparison
  71. 71. Україна (in Ukrainian) Украина (in Russian) Ukraine (in English) Nodes 3223 17964 29647 Edges 3160 21107 27854 Density 0.000304 0.000065 0.000031 Diameter 29 39 61 Reciprocity 0.026 0.057 0.029 Modularity 0.85 0.78 0.89 Anatoliy Gruzd 76@gruzd Cross Network Comparison
  72. 72. Україна (in Ukrainian) Украина (in Russian) Ukraine (in English) Nodes 3223 17964 29647 Edges 3160 21107 27854 Density 0.000304 0.000065 0.000031 Diameter 29 39 61 Reciprocity 0.026 0.057 0.029 Modularity 0.85 0.78 0.89 Anatoliy Gruzd 77@gruzd Cross Network Comparison
  73. 73. #Diplometrics (Day 1) Node size = In-degree centrality
  74. 74. Україна (in Ukrainian) Украина (in Russian) Ukraine (in English) #Diplometrics (Day 1) Nodes 3223 17964 29647 140 Edges 3160 21107 27854 322 Density 0.000304 0.000065 0.000031 0.017 Diameter 29 39 61 9 Reciprocity 0.026 0.057 0.029 0.162 Modularity 0.85 0.78 0.89 0.39 Anatoliy Gruzd 79@gruzd Cross Network Comparison
  75. 75. #Diplometrics (Day 1) Node size = In-degree centrality Interactive: http://bit.ly/diplonet16 Animated http://bit.ly/diplonet16live
  76. 76. Outline • Background • Social Media Use during the 2014 EuroMaidan Revolution • Review of Social Media Platforms • VKontakte • Twitter • Current & Future Challenges in Social Media Analytics 81@gruzd Anatoliy Gruzd
  77. 77. (1) Current & Future Research Challenges: Social Media Data Analytics Tools
  78. 78. Cloud & Distributed Computing Data & Information Organization Analytics Visualization (1) Current & Future Research Challenges: Social Media Data Analytics Tools @gruzd Anatoliy Gruzd 83
  79. 79. to introduce these emerging tools & techniques to diplomats who are increasingly relying on social media data as their go-to data source! The challenge is ... © Chris Allen licensed under Creative Commons
  80. 80. (1) Current & Future Research Challenges: Social Media Data Analytics Tools @gruzd Anatoliy Gruzd 85 Netlytic – a web-based text and network analysis tool http://netlytic.org
  81. 81. @gruzd Anatoliy Gruzd 86 Social Media Analytics Toolkit http://socialmedialab.ca/apps/social-media-toolkit/
  82. 82. (2) Current & Future Research Challenges: The Rise of Social Bots: Reported & Estimated % of Fake Accounts Fake 5% Fake 2% Fake 8% Source: http://blogs.wsj.com/digits/2015/06/30/fake-accounts-still-plague-instagram-despite-purge-study-finds/ 1.5B users 300M users 400M users … but is that everything? @gruzd Anatoliy Gruzd 87
  83. 83. (2) Current & Future Research Challenges: The Rise of Social Bots • Who are we studying? • Humans or Bots? Anatoliy Gruzd 88@gruzd @gruzd Anatoliy Gruzd 88
  84. 84. (2) Current & Future Research Challenges: The Rise of Algorithmic Filtering • What are we studying? • Human behaviour or Algorithms? Anatoliy Gruzd 89@gruzd @gruzd Anatoliy Gruzd 89
  85. 85. Takeaways 91 • Network-level indicators, such as modularity index and average engagement level, could help to classify and describe online groups based on their network structures. • A combination of SNA, visualization and community detection algorithm, coupled with a manual content analysis of a sample of group messages and user profiles is an effective approach to study the underlying social structures of online groups and campaign. • Need to perform a multi-platform analysis • Need to know who and what types of networks we are analyzing: Friendship vs Communication networks @gruzd Anatoliy Gruzd
  86. 86. Photo credit: Karl Schönswetter #OccupyGezi: Gezi Parki Protest, Turkey (2013) 92 #OccupyGezi Supporters in Victoria, BC ? Broad Implications: Can we predict a successful social campaign/movement? Can we predict group/movement’s longevity? @gruzd Anatoliy Gruzd
  87. 87. PUBLIC DIPLOMACY FOR THE SOCIAL MEDIAAGE ANATOLIYGRUZD (@GRUZD) Ottawa, Canada April 21, 2016 Canada Research Chair in Social Media Data Stewardship Associate Professor, Ted Rogers School of Management Director of the Social Media Lab Ryerson University

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