Social media grants us convenience. On-the-go news is churned out and accessible through a few clicks and choice hashtags. As we make our fast food orders whilst an incident occurs on the other side of the world, we can be made aware of it quicker than our orders are wrapped up to go by merely browsing on our phones.
And in order to stay current with the evolution of global communication, most publishing houses need to keep up. This is the same for scientific media. And indeed, social media for science communication does have its merits. With popular websites like IFLS and New Scientist making research findings more accessible to a lay audience, this is an age where we literally have science at our fingertips. All it takes is one tap.
However, sometimes the message gets muddled due to clickbait headlines. But clickbait sells. And money is the ultimate endgame for most media houses.
So what exactly happens when science communication goes wrong somewhere? One highly infamous case which began pre-social media still plays out in the comments section of facebook till date. Nearly twenty years ago Andrew Wakefield released fraudulent results linking the MMR vaccine to autism. The ensuing sensationalism has led to catastrophic consequences still felt today. One only need use the Google search engine to find blogs and websites dedicated to the opposing sides of the vaccination argument. With mounting frustration on both sides, scientists and science communicators no doubt realise that this media storm could have been quelled had the initial route of ‘science by press release’ been avoided. This case also emphasizes how critical robustness of scientific data is. If anything, we have learned that scientists, their perceptions, and the communication of their findings thereafter have a significant global impact. And with the advent of social media, this has only increased.
There have been instances where flawed methodologies, and consequently flawed findings, are reported and feed into prejudice. Take for instance the 2011 article published by Dr. Satoshi Kanazawa in Psychology Today entitled, ‘why are black women less physically attractive than other women?’ However puzzling it may be that such a subjective article could pass through the editorial process of a reputable online magazine, this is by no means the first time science has been used to justify racism.
One such incident in which scientific study was embarked upon at the cost of African Americans was the Tuskegee syphilis study. Over a forty year period beginning in 1932 hundreds of African-American men, many of whom did not know they had syphilis, were enrolled into the study. Not only were they intentionally misled concerning their ailment, but they were also left untreated even when penicillin became a standard syphilis treatment. Entire families were affected. And this is just one example of why black and ethnic minority groups are justified for any feelings of wariness regarding scientific research that specifically includes them as a study cohort.
Since then, science has come a long way in terms of ethical standards. Protocol now requires that ethics boards preside over applications for permission to do research involving humans or animals. Furthermore, informed consent is required from all human participants. Still, because of shortcomings of the past, the scientific community has trust to gain from the general public. One way to gain this trust is through scientific transparency, and this is where social media comes in.
Considering that we live in an age of ‘fake news,’ unbiased science communication is needed more than ever. And this extends to the 140 character-limit allowed on twitter. One example to highlight what can go wrong when a science publishing house tweets erroneously is the case of the New Scientist website and Serena Williams. The April 2017 tweet from New Scientist contained a link to their article and video on Serena Williams entitled, ‘How pregnancy could affect an elite athlete like Serena Williams.’
While the article itself explored the possibility of pregnancy potentially contributing to an athlete’s performance, the conclusion drawn was that there is not much evidence to support this theory. The problem however lay in the headline of the New Scientist tweet: ‘Could pregnancy have helped Serena Williams win the Australian Open?’ This question format could already elicit a subjective response in readers. Further, in the one-minute video clip attached to this tweet, only in the second part was it explained that pregnancy likely did not help Serena Williams in any way. As standard practice in the science community is to use conclusive headlines and avoid clickbait, many black and ethnic minority social media users were left disappointed by the manner in which New Scientist circulated this particular story. This, especially in light of the fact that the New Scientist twitter timeline usually does practice using conclusive headlines.
Andrew Wakefield and the MMR vaccine scandal, Dr. Satoshi Kanazawa, and New Scientist and Serena Williams are three distinct examples that respectively show the progression from willful reporting of false data, to flawed methodologies leading to subjective reports in articles, and a well-intentioned article that carried racial undertones due to a clickbait tweet. Their commonality lies in the fact that they all chip away at scientific credibility in the public eye. Further, racism in science alienates black and ethnic minority groups who have historical precedence for being wary about scientific practice. In this age where in spite of research advancements there are still as many gaps to be filled, the science community simply cannot afford for this to happen. And while science continues to evolve, the field of science communication is perfectly situated to bridge the gap between scientists, their findings, and the general public.
In itself, social media for science communication is not the problem. Quick-fire hot-takes are.
There need to be check points to ensure that research, and its limitations, is accurately and reliably communicated. Science communication via social media needs to mirror the stringency of the peer-review process. Because while 280 characters on twitter may not necessarily provide the space to develop sound scientific arguments, nuance is required to keep the headline true to the message or it will be lost in clicks and retweets faster than you can say ‘McScience’.