The Rise of Patient Communities on Twitter – Twitter Visualized

For over 2 years, Symplur has collected health conversations on Twitter. From a humble start, our infrastructure has grown and matured to scale with the tremendous growth of healthcare social media. We’re now approaching 150 million health tweets in our database which we analyze and categorize by thousands of variables. And similarly with other repositories of big data, our greatest challenge is to figure out how to present insights from such a vast dataset in a meaningful way. The answer is often found in visualizations.

We plan to start a small series of short posts displaying some of this data in a visual way.

What you see in the video below is a 22-month timeline of about 2,000 different health communities and topics each visualized as a bubble. In total, about 100 million healthcare tweets are represented in this visual. The green dots symbolize patient-centric topics, while pink encompasses more professional/provider topics. Larger bubbles signify larger volume of conversations within that community. The data is visualized dynamically over the this 22-month time period starting September 2010.

 

 

Why the growth of Patient Communities on Twitter?

What we discovered was somewhat of a surprise. From the start, many considered Twitter as a kind of virtual water cooler, mostly used by healthcare professionals. It’s been thought that the need for privacy would push patients to more closed platforms. Twitter as you know, is totally public and should not be considered private.

However, from what you can clearly observe, the green bubbles have grown in numbers and significance quite dramatically in past months. This indicates a strong growth of conversations in existing patient communities on Twitter and also a growth of new patient communities on Twitter within our dataset.

Why this growth? Why would patients choose to utilize a communication platform without privacy? We will continue this visual journey trying to give possible answers to that question.

 

Update: The second post in this series is now published –  The Dynamics of a Twitter Patient Community – Network Centrality Analysis

Audun Utengen

Audun Utengen - @audvin

Sharing research from the Healthcare Social Graph®. Co-founder, CEO of @symplur. Advisor to @MayoClinicSMN. ❤️ #Parkinsons, #Schizophrenia, #PancreaticCancer

173 Responses to “The Rise of Patient Communities on Twitter – Twitter Visualized”

  1. Jodi Sperber

    Great visualization. Thank you! I am not particularly surprised that patients are using this as a means of communication, even though it is not a private space. People are looking to connect, and the public space allows this to happen more organically. I also have a feeling that ease of use has something to do with it – there is little to learn aside from the platform specific lingo (@, #, RT, etc) and once that hurdle is crossed it is fairly simple to participate.

    Reply
    • Audun Utengen

      Audun Utengen, MBA

      Thank you Jodi.

      I’m in complete agreement with you, especially regarding the “organic” attribute. I will talk to that important point in the next post in this series.

      I’ve also been in the belief that one of the major attractions with Twitter for patients is exactly that it is without privacy! With no privacy comes complete transparency. With transparency comes discoverability. And since 1 in 5 patients are looking for people online with same condition (PEW), discoverability wins!

      There is a case to be made for Twitter and there is a case to be made for closed anonymous forums. Both serve a distinct job-to-be-done that will not disappear regardless of whatever technology will come and go.

      Reply
  2. Robert West PhD

    Nice! RT @audvin: RT @symplur: The Rise of Patient Communities on Twitter – Twitter Visualized by @audvin http://t.co/JgM2VAoQ #hcsm #pm101

    Reply
  3. Kati Debelic

    Nice! RT @audvin: RT @symplur: The Rise of Patient Communities on Twitter – Twitter Visualized by @audvin http://t.co/JgM2VAoQ #hcsm #pm101

    Reply
  4. Audun Utengen

    Thanks :) RT @westr: Nice! RT @symplur: The Rise of Patient Communities on Twitter – Twitter Visualized http://t.co/QrDseYOg #hcsm #pm101

    Reply
  5. Joe Capizzi

    Thanks :) RT @westr: Nice! RT @symplur: The Rise of Patient Communities on Twitter – Twitter Visualized http://t.co/QrDseYOg #hcsm #pm101

    Reply
  6. Cherise/LADA

    Thanks :) RT @westr: Nice! RT @symplur: The Rise of Patient Communities on Twitter – Twitter Visualized http://t.co/QrDseYOg #hcsm #pm101

    Reply
  7. Audun Utengen

    Thanks for you comment @jsperber :) The Rise of Patient Communities on Twitter – Twitter Visualized http://t.co/Ye8Z0ORr #hcsm #hcsmanz

    Reply
  8. Lisa Fields

    Thanks for you comment @jsperber :) The Rise of Patient Communities on Twitter – Twitter Visualized http://t.co/Ye8Z0ORr #hcsm #hcsmanz

    Reply
  9. Ali R. Jalali

    The Rise of Patient Communities on Twitter – Twitter Visualized #cphc #hcsm #ePatient http://t.co/vxL54pMQ

    Reply
  10. Colleen Young

    Interesting visualization Audvin. However, I question the separation of patient and provider communities. Where for example does the #hcsm and its geo-chapters fit in? I, for one, do not consider #hcsmca to be either patient- nor provider-centric. Our mission is to dismantle such silos and I believe my fellow #hcsm-chapter founders make the same effort. There are several other chats in which I participate (i.e., #hpm, #eolchat and even #bcsm) where I would be hard pressed to define as patient or provider.

    The beauty of Twitter is the intersection and confluence of people of all stripes. While I appreciate what this data demonstrates, I look forward to the day that we no longer need to make such a distinction.

    How were the #hcsm chapters categorized?

    Reply
    • Audun Utengen

      Audun Utengen, MBA

      Hi Colleen!

      Indeed, one of the major attractions of Twitter has been its force of removing boundaries of all kinds. A spot in the world where all users are created equal, individuals and organizations alike. This force extends to geographical and professional boundaries.

      All the “#hcsm”s were categorized as “professional/provider topics”. There is no true black and white (or should we say green/pink), but segmentation will always be very helpful to paint a picture of what is taking place. In the next couple of blogs in this series we will take a closer look at a couple of these patient centric communities. From looking at the dynamics of these communities, and then a closer look at the members, we will talk directly to this point. Stay tuned!

      Reply
  11. Louise Aronson

    Productive pandemic MT@ARJalali: The Rise of Patient Communities on Twitter – Twitter Visualized #cphc #hcsm #ePatient http://t.co/seFwrQaT”

    Reply
  12. Isaac Thangasamy

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    Reply
  13. Thomas M. Lee

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    Reply
  14. Gustaf von Dewall

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    Reply
  15. JOHN NOSTA

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    Reply
  16. JOHN NOSTA

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    Reply
  17. Aurora

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    Reply
  18. Steven Tucker, MD

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    Reply
  19. Brian S. McGowan PhD

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    Reply
  20. Brian S. McGowan PhD

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    Reply
  21. Graham Steel

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    Reply
  22. Mike Thompson, MDPhD

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    Reply
  23. Anne Sorensen

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  25. Michelle Lemme

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  26. Glenn Lanteigne

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  27. Glenn Lanteigne

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  28. Open Science Fedn

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    Reply
  29. Ian Mclean

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  30. Derek Warnick

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    Reply
  31. Robert West PhD

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    Reply
  32. Graham Steel

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    Reply
  33. Viktor Trón

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    Reply
  34. Graham Steel

    @PaulLikeMe Me thinks you'll find this of interest, generally http://t.co/r9Ry8YTR #hcsm

    Reply
  35. Ali R. Jalali

    Interesting visual of Rise of Patient Communities on Twitter – #cphc http://t.co/3t1uENhX – How can we help these communities? Via @ARJalali

    Reply
  36. Dvorah Graeser

    Rise of #Patient Communities on Twitter Visualized – http://t.co/O6ChmWyz

    Reply
  37. Dvorah Graeser

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    Reply
  38. Ritesh Patel

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    Reply
  39. Ritesh Patel

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    Reply
  40. George Van Antwerp

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    Reply
  41. Jen Dyer MD, MPH

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    Reply
  42. Eric Rumsey

    The Rise of Patient Communities on Twitter … Visualized http://t.co/gtcNIb64@symplur: @audvin MT @westr

    Reply
  43. AnneMarie Cunningham

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    Reply
  44. Andrew Spong

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    Reply
  45. Andrew Spong

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  46. Andy Hayley

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  47. Zoe Tabary

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  48. Paul Tunnah

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  49. Lilly Clinical OI

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    Reply
  50. Inhaled Oxytocin PPH

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  51. Iain Scott

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    Reply
  52. Iain Scott

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    Reply
  53. Albert Redondo

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    Reply
  54. Blue Shield of CA

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  55. Blue Shield of CA

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  56. Joyce Lee

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    Reply
  57. Joyce Lee

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  58. Joyce Lee

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  59. Joyce Lee

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  60. Regina Holliday

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    Reply
  61. Regina Holliday

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    Reply
  62. Shannon Ragland

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    Reply
  63. Matthew Katz

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    Reply
  64. Digital Health Com

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  65. Keith Schorsch

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  66. Keith Schorsch

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    Reply
  67. Michael Josefowicz

    video is a 22-month timeline of about 2,000 different health communities and topics each visualized as a bubble. http://t.co/qXSvoFcM

    Reply
  68. Michael Josefowicz

    The Rise of Patient Communities on Twitter – Twitter Visualized http://t.co/aUfNqqtR

    Reply
  69. Berci Meskó, MD, PhD

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    Reply
  70. HSAMatRobertMorrisU

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    Reply
  71. Cathy Ure

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    Reply
  72. Red Salud Andalucía

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    Reply
  73. Sumardy

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  74. Elizabeth Bailey

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  75. Reed Smith

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  76. Thomas M. Lee

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  77. Maria Jose Alonso

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  80. White Space HCM

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    Reply
  81. Bangor Beacon

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  82. Chris Goldrick

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  83. BurrillDigitalHealth

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  84. Helen Haskell

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    Reply
  85. Pediculosis Assoc

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    Reply
  86. Pediculosis Assoc

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    Reply
  87. Paul Boidy

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    Reply
  88. Mark Greenwood

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    Reply
  89. Ritesh Patel

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    Reply
  90. Ashley Wetmore

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    Reply
  91. Healthcare IS

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    Reply
  92. DavidKushan

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    Reply
  93. Lindsay Lemire

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    Reply
  94. Wayne W.Xu

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    Reply
  95. Joseph Babaian

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    Reply
  96. Harris Lygidakis

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    Reply
  97. Michael Davidson

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    Reply
  98. EHICCIOCampaign

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    Reply
  99. Kathy Meyer 

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    Reply
  100. Michael Spitz

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    Reply
  101. Mike Reno

    The Rise of Patient Communities on Twitter – http://t.co/bFWXbcs2 via @symplur Voice of the Customer is alive #TEAMwork

    Reply
  102. Mark Harmel

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    Reply
  103. Mark Harmel

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    Reply
  104. Jon Mertz

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    Reply
  105. Richard Anderson

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    Reply
  106. Howard Rosen

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    Reply
  107. Clinical Advisor

    RT @elaineschattner: Via @bacigalupe: The Rise of Patient Communities on Twitter, visualized – http://t.co/NxX6sHpG

    Reply
  108. DeeAnna Nagel

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    Reply
  109. Derf

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    Reply
  110. Danny Fries

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    Reply
  111. Dr. Pénzes János

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    Reply
  112. SashaKane

    Via @bacigalupe: The Rise of Patient Communities on Twitter, visualized – http://t.co/975iG4iS

    Reply
  113. Mike Thompson, MDPhD

    The Rise of Patient Communities on Twitter – Twitter Visualized – @Audvin via @Symplur http://t.co/TH6xJdX3

    Reply
  114. Howard Luks MD

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    Reply
  115. Mike Painter

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    Reply
  116. H2Online

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    Reply
  117. Heather Marie Nash

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    Reply
  118. KRHDHealthLaw

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    Reply
  119. Noble Vision Group

    RT @drpenzesjanos What does 100 million health tweets look like? Twitter Visualized http://t.co/wgr2XSWK #hcsmeu #socpharm

    Reply
  120. Kim Henshaw

    Just stumbled across this great post about how patients are leading the healthcare exchanges on SoMe cc: @audvin http://t.co/NcskHwao

    Reply
  121. Sam Bruinewoud

    Geeking out on #hcsm and data visualisations, thank you @symplur ! http://t.co/dB96barv

    Reply
  122. Audun Utengen

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    Reply
  123. Thomas M. Lee

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    Reply
  124. Dr. Dewey Jones IV

    The Rise of Patient Communities on Twitter – Twitter Visualized http://t.co/mLFXGkNY #hcsm

    Reply
  125. Markoneinfour

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    Reply
  126. Trevor Lakey

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    Reply
  127. Jo

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    Reply
  128. Richard McCrea

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    Reply
  129. Tek Doz Dijital

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    Reply
  130. Harun Kurt

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    Reply
  131. Lisa Fields

    Almost 150 million health tweets in @symplur database
    Rise of Patient Communities=Twitter – Twitter Visualized
    http://t.co/mc0K5XJ3
    #HCLDR

    Reply
  132. Ann Bartlett

    Almost 150 million health tweets in @symplur database
    Rise of Patient Communities=Twitter – Twitter Visualized
    http://t.co/mc0K5XJ3
    #HCLDR

    Reply
  133. Lisa Fields

    Almost 150 million health tweets in @symplur database Rise of Patient Communities=Twitter – Twitter Visualized http://t.co/mc0K5XJ3#HCSM

    Reply
  134. Lisa Fields

    Almost 150 million health tweets in @symplur database Rise of Patient Communities=Twitter – Twitter Visualized http://t.co/mc0K5XJ3#HCSM

    Reply
  135. Alex Riegler, EMPH

    Almost 150 million health tweets in @symplur database Rise of Patient Communities=Twitter – Twitter Visualized http://t.co/mc0K5XJ3#HCSM

    Reply
  136. Françoise L'HEVEDER

    Almost 150 million health tweets in @symplur database Rise of Patient Communities=Twitter – Twitter Visualized http://t.co/mc0K5XJ3#HCSM

    Reply
  137. Bernhard Danzer

    Almost 150 million health tweets in @symplur database Rise of Patient Communities=Twitter – Twitter Visualized http://t.co/mc0K5XJ3#HCSM

    Reply
  138. Ali R. Jalali

    Almost 150 million health tweets in @symplur database
    Rise of Patient Communities=Twitter – Twitter Visualized
    http://t.co/mc0K5XJ3
    #HCLDR

    Reply
  139. Lisa Fields

    Thanks @AnnBartlett 4 Tweet MT Almost 150 million health tweets in @symplur database Twitter Visualized http://t.co/mc0K5XJ3 …cc: @symplur

    Reply
  140. Mike Thompson, MDPhD

    The Rise of Patient Communities on Twitter – Twitter Visualized http://t.co/fl4xcBP0 via @Symplur

    Reply
  141. Anas Younes, M.D.

    Very interesting…RT @mtmdphd: The Rise of Patient Communities on Twitter – Twitter Visualized http://t.co/KVlvXkY4 via @Symplur

    Reply
  142. Dr. Luis Villela

    The Rise of Patient Communities on Twitter – Twitter Visualized http://t.co/fl4xcBP0 via @Symplur

    Reply
  143. Treato

    Awesome visuals of the rise of twitter patient communities http://t.co/204SDAed

    Reply
  144. QuantifiedSelfTrends

    The rise of patient communities: visualized http://t.co/5PwM2B6M

    Reply
  145. The Rise of Patient Communities on Twitter - Twitter Visualized | Internet Medicine | Scoop.it

    […] For over 2 years, Symplur has collected health conversations on Twitter. From a humble start, our infrastructure has grown and matured to scale with the tremendous growth of healthcare social media. We’re now approaching 150 million health tweets in our database which we analyze and categorize by thousands of variables. And similarly with other repositories of big data, our greatest challenge is to figure out how to present insights from such a vast dataset in a meaningful way. The answer is often found in visualizations…  […]

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  146. openingscience.org

    […] the Rise of Patient Communities on Twitter. Have a look here for […]

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  147. The Rise of Patient Communities on Twitter | Sa...

    […] Twitter Visualized The Rise of Patient Communities on Twitter The Dynamics of a Twitter Patient Community – Network Centrality Analysis The Fl  […]

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  148. Physician Storytelling: Facilitating Meaningful Change

    […] and monitor it. In addition, social media has made it possible for patients to come together, form communities, and provide support for one another in ways never previously […]

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  149. The dynamics of a Twitter Patient Community - Network Centrality Analysis

    […] our previous post we looked at the growth of patient-centric conversations on Twitter visually identified in our healthcare dataset as green nodes. This time, we’re going to zoom […]

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