This document describes a project to automatically generate tweets about medical research studies and news to help spread information to disease communities on Twitter. The system, called Science Connect, scans databases of research publications, clinical trials, and university news to find relevant disease-specific content and tweets about it using hashtags. In an initial test over 10 months, the Science Connect Twitter accounts gained over 1,500 followers and tweeted over 2,000 times. The tweets received over 1,100 clicks from users and over 100 retweets or mentions, suggesting it helped spread research information to interested audiences. Feedback from communicators was positive about the time it saved them in disseminating research. Further analysis is needed to fully assess the reach and benefits of different types

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. The Challenge…

3. Research
can...

4. ...help patients learn
about their disease

5. ...and inform about
latest treatments
options.

6. But research
can only help...

7. ...if people
know about it.

8. Wouldn t it be great...

9. ...if more people
knew about research?

10. What we did…

11. We created a
technology that
automatically finds
topic-specific
research & news…

12. ...and creates tweets.

13. ...to help us reach
disease communities
and others on Twitter.

14. Why Twitter?

15. Because Twitter
already includes
thousands of
people…

16. …who are part of active
disease communities.

17. How do we know?

18. For example,
within a 24-hour period
there were…

19. 1,500 tweets posted
using #diabetes;
reaching 1.6 million
Twitter users
Source: Hashtracking.com, Oct 8th, 2012

20. …making it easy to
find and participate
in disease-related
conversations.

21. How does
work?
Science Connect

22. Research-Related News

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. Science Connect
automatically scans data sources
for disease-specific content
Research-Related News

25. Science Connect
automatically scans data sources
for disease-specific content
Research-Related News

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. What s also
really neat is...

28. ...users are notified
when a new tweet
has been
created…

29. ...and the tweet is
automatically posted
to the assigned
Twitter account.

30. Editing a tweet
is easy too.

31. Preliminary Results

32. Phase 1
After 6 weeks…

33. We had launched 8
UCSF disease research
Twitter accounts.

34. https://twitter.com/UCSFRemix/ucsf-disease-research/members

35. Sep 15, 2013

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. 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. Phase 2
After 10 months…

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. Feedback we received so far…

44. 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

45. 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

46. 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

47. 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

48. 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.
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