Twitter’s Reaction to Covid-19 and HIMSS20
In March, we were excited about attending the HIMSS 2020 Global Conference & Exhibition and had put in a lot of effort to get ready to tell attendees all about our AI work in Medical Information and the exciting work we are pioneering with leading biopharmaceutical and healthcare companies like Biogen, Sage Therapeutics and NCR, including:
- creating chatbot-like systems that help medical information offices more accurately and quickly answer constituent questions about treatments and therapies
- running Voice of the Patient and Key Opinion Leader programs
- aiding in regulatory compliance and medical coding
- developing new machine learning models and predictive question answering that are making the jobs of CMIOs and CMOs easier and improving patient care
Unfortunately, Covid-19 had different plans. When conferences from Facebook F8 to Google I/O started cancelling, we could see the writing on the wall for HIMSS…actually, we could see the tweets in the Twitterverse.
As the week went on, HIMSS attendees and exhibitors were taking to Twitter to voice their opinions about HIMSS’ apparent decision to go on with the show, and since we’re in the business of AI-driven natural language processing and sentiment analysis, we put our tools to work and dug into the data. Here’s what we found people were tweeting about in the days leading up to the cancellation announcement:
We analyzed 6481 tweets total covering the period 2/24/2020 – 3/5/2020 that included the hashtags #HIMSS20 and #HIMSS2020
- 830 or 12.8% expressed concern about coronavirus, 582 or 10.5% mentioned cancellation, 160 or 3% mentioned the president, 124 or 2% mentioned interoperability
- 35% positive, 58% neutral, 7% negative
Today in some areas of the country we are weeks into social distancing or sheltering-in-place in efforts to “flatten the curve” which shows that early predictions of the advisability of cancellation were well placed. So even though we may have missed you at HIMSS this year, we’re here to chat about creating meaning out of your text data and helping you deliver results.
