Why we tweet

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We use twitter to share recent publications that are informing the science we do in the lab. Anyone curious about the state of our field, can quickly look through our twitter stream for papers that catch their interest. If more people shared publications, it would be easier to enter new fields, stay broadly educated and to identify high impact publications without relying on journal reputations. I believe that transformative science starts with ideas informed by a broad knowledge base. Staying on top of developments in a range of fields is challenging, because the rate of publishing produces a glut of publications that are difficult to shift through. Searching the literature through Pubmed requires that you know what to query and typically produces more results than you can realistically read. How do you sort through all of the papers outside of your field?

Most people, if they are like me, shift through Pubmed results using a very biased approach. Often the quality and potential importance of a publication is determined by looking at the researchers involved and the name of the journal. High impact publications can be easily missed.

I have a better way, and it involves crowd sourcing and twitter. Yes, scientists shun social media, and crowd sourcing sounds vague and modish, but hear me out.

My lab publicly shares a list of publications that we are reading and are relevant to the focus of our lab's research. To host our list, we use Twitter, because it is very easy to use and distribution is automatic. Other scientists can follow us through their twitter accounts and the list is dynamically updated on our website.

Imagine if every lab posted a list of the publications they are reading on their webpage. You could quickly get up to date in a subfield simply by monitoring what labs in that field are reading. If you are considering starting a collaboration with a group or thinking of applying for a postdoctoral position in a new field, it would be easy to browse the relevant and recent literature. More broadly, if a large number of labs shared their reading lists, computational algorithms could analyze these twitter feeds. The real-time impact of each publication could be automatically determined by calculating which papers inform the most labs.

Of course, this is just a dream and a long ways off. But we are starting it here. I hope that others will create twitter feeds for themselves or their labs that list the papers they are reading. Please let me know if you do!