spreading science, one automated tweet at a time
DESCRIPTION
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.TRANSCRIPT
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
The Challenge…
Research can...
...help patients learn about their disease…
...and inform about latest treatments options.
But research can only help...
...if people know about it.
Wouldn’t it be great...
...if more people knew about research?
What we did…
We created a technology that
automatically finds topic-specific
research & news…
...and creates tweets.
...to help us reach disease communities and others on Twitter.
Why Twitter?
Because Twitter already includes thousands of people…
…who are part of active disease communities.
How do we know?
For example, within a 24-hour period
there were…
1,500 tweets posted using #diabetes;
reaching 1.6 million Twitter users
Source: Hashtracking.com, Oct 8th, 2012
…making it easy to find and participate in disease-related
conversations.
How does
work?
Science Connect
Research-Related News
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
Science Connect automatically scans data sources for disease-specific content
Research-Related News
Science Connect automatically scans data sources for disease-specific content
Research-Related News
Science Connect automatically scans data sources for disease-specific content
…and creates tweets using disease-specific #hashtags and shortened URLs.
Research-Related News
What’s also really neat is...
...users are notified when a new tweet has been created…
...and the tweet is automatically posted to the assigned Twitter account.
Editing a tweet is easy too.
Preliminary Results
Phase 1
After 6 weeks…
We had launched 8 UCSF disease research
Twitter accounts.
https://twitter.com/UCSFRemix/ucsf-disease-research/members
Sep 15, 2013
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
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
Phase 2
After 10 months…
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
Feedback we received so far…
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
“
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
“
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
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
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 Inbox Video: http://www.youtube.com/watch?v=5nt3gE9dGHQ