Posted: August 28, 2016, 6:12pm
I recently realized the power of social media for science. Yes, I also realize how ridiculous that sounds. Science is serious. Taking selfies on Snapchat is not so serious. But a few things recently broadened my mind to try to harness the power of the social web for the good of science. Let me explain.
To share or not to share?
I travelled 5,348 miles from Los Angeles to the tiny town of Nottingham in Northern England this summer to go to a math biology conference. I presented a few of my math models of tumor progression and chemotherapeutic resistance. To my surprise, one of the hot topics of debate at the conference was the ability to share pictures of the plenary talks on social media. Apparently, many researchers have adopted the strategy of blogging or tweeting (or both!) during the conferences.
But very often, researchers are afraid of getting ‘scooped’ when someone else publishes a similar research article just before. Credit usually goes to the first, even if two people are working simultaneously. So the idea of someone in the audience snapping pictures and posting them for the world to see is terrifying to some. Others, adopted a more inclusive strategy, relying on Twitter or blogging platforms to bounce around ideas that aren’t fully formed, or to accepted feedback on published ideas.
The conference dealt with this opposition of opinions by giving the presenters a choice of social share or not-share. Each presenter posted a slide in the beginning indicating their preferences.
FOMO or fo-sho?
After I finished my talk I had about 90 new downloads on my new publication in IOP Scienceand a dozen new Twitter followers. Even a few months later, I’m starting to realize the benefits of connecting with these collaborators. Just yesterday, one of the researchers I met in Nottingham sent me a link to a postdoc position that I might be interested in!
Science of Scientists
A good scientist can’t help but analyze data. At this conference, a hashtag was used to communicate (#ECMTB2016). So naturally, someone did an R analysis of the tweets to figure out who the popular tweets were and what they were tweeting about. This is the kind of nerdiness I can really get behind! Scroll down to see what @tek_keller came up with. Original tweet here.
Published on July 25th, 2017
Last updated on August 10th, 2017