Spreading Science, One Automated Tweet At A Time

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We experimented with an automated social media approach to disseminate research more widely and engage with disease communities. Here we share our results and feedback we received from the academic community and patients. We hope to contribute to rethinking scientific outreach where academic research institutions take on a more proactive role.

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Spreading Science, One Automated Tweet At A Time

  1. 1. Spreading Science, One Automated Tweet At A Time Katja Reuter1, PhD, and Anirvan Chatterjee2 Bradley Voytek3, PhD, John Daigre1 1 Southern California Clinical and Translational Science Institute (SC CTSI), University of Southern California (USC) 2 Clinical and Translational Science Institute (CTSI at UCSF), University of California, San Francisco (UCSF) 3 University of California, San Francisco (UCSF), Department of Neurology Presented to CTSA Communications Key Functions Committee group, Sep 18, 2013
  2. 2. The Challenge…
  3. 3. Research can...
  4. 4. ...help patients learn about their disease
  5. 5. ...and inform about latest treatments options.
  6. 6. But research can only help...
  7. 7. ...if people know about it.
  8. 8. Wouldn t it be great...
  9. 9. ...if more people knew about research?
  10. 10. What we did…
  11. 11. We created a technology that automatically finds topic-specific research & news…
  12. 12. ...and creates tweets.
  13. 13. ...to help us reach disease communities and others on Twitter.
  14. 14. Why Twitter?
  15. 15. Because Twitter already includes thousands of people…
  16. 16. …who are part of active disease communities.
  17. 17. How do we know?
  18. 18. For example, within a 24-hour period there were…
  19. 19. 1,500 tweets posted using #diabetes; reaching 1.6 million Twitter users Source: Hashtracking.com, Oct 8th, 2012
  20. 20. …making it easy to find and participate in disease-related conversations.
  21. 21. How does work? Science Connect
  22. 22. Research-Related News
  23. 23. For example… ü  Publications from PubMed ü  Clinical trials information from ClinicalTrials.gov ü  Tweets from researchers and University groups ü  University research news from University Relations ü  Researchers’ profiles
  24. 24. Science Connect automatically scans data sources for disease-specific content Research-Related News
  25. 25. Science Connect automatically scans data sources for disease-specific content Research-Related News
  26. 26. Science Connect automatically scans data sources for disease-specific content …and creates tweets using disease-specific #hashtags and shortened URLs. Research-Related News
  27. 27. What s also really neat is...
  28. 28. ...users are notified when a new tweet has been created…
  29. 29. ...and the tweet is automatically posted to the assigned Twitter account.
  30. 30. Editing a tweet is easy too.
  31. 31. Preliminary Results
  32. 32. Phase 1 After 6 weeks…
  33. 33. We had launched 8 UCSF disease research Twitter accounts.
  34. 34. https://twitter.com/UCSFRemix/ucsf-disease-research/members
  35. 35. Sep 15, 2013
  36. 36. After 6 weeks After 10 months Total number of followers 867 Total number of tweets sent 1,042 Number of clicks by Twitter users 1,149 Number of mentions and retweets by Twitter users 106
  37. 37. Retweets from other UCSF Twitter account PubMed research papers Other (University research news clinical trials) Researchers’ Profiles What people clicked on 1.54 1.00 0.89 0.64 Clicks per tweet
  38. 38. Phase 2 After 10 months…
  39. 39. After 6 weeks After 10 months Total number of followers 867 2,381 Total number of tweets sent 1,042 2,000 Number of clicks by Twitter users 1,149 Analysis ongoing Number of mentions and retweets by Twitter users 106 Analysis ongoing
  40. 40. Feedback we received so far…
  41. 41. UCSF Science Connect is a great time saver. It helps us by making sure that we don t miss the latest HIV research conducted at UCSF that s potentially relevant and interesting to our audience. Michael Bare, Research Communications Specialist, Center for AIDS Prevention Studies, UCSF
  42. 42. I jumped at the chance to use UCSF Science Connect!  Automating the information- finding step is a great plus for communicators, and the smart hashtagging not only gets the info to a wider audience, it educates us all on leveraging the power of the medium. Karen Gehrman, Interim Communications Manager, Helen Diller Family Cancer Center, UCSF
  43. 43. q  We can increase the reach of research by using social media and connect with disease communities. q  Automation is not necessarily a bad thing if it is made clear to audience. q  Using such an approach, communicators can save time and increase their output. What we learned
  44. 44. q  More research is necessary to assess q  the reach of different types of content to benefit diseases communities. q  what content serves disease communities best. q  if such an approach strengthen an institution’s research brand. q  if such an approach can foster research participant recruitment? Next steps
  45. 45. Thanks! This project was funded through an IT Innovation Contest Award from the University of California, San Francisco (UCSF) and supported by the Clinical and Translational Science Institute (CTSI) at UCSF. Images adapted from Google’s Gmail Priority InboxVideo: http://www.youtube.com/watch?v=5nt3gE9dGHQ

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