So a few months ago, I was fortunate enough to be asked to give a talk at the Nature Careers Expo in London about how to use social media to build scientific communities. As part of this, there was a short panel discussion afterwards with myself and Sarah Blackford from the Society for Experimental Biology, and Nature have made a few short videos of some of the responses available!
This was originally posted at: http://blogs.egu.eu/palaeoblog/?p=1232
“Postpublication peer review on social media is like the mosh pit at a punk rock conference. It’s fast, uncoordinated, a lot less subtle, more in your face, and involves a few more risks.’
Peer review is the cornerstone of scientific legitimacy – it is the process where research is analysed by your professional peers. Traditionally, this has been conducted before the publication of an article. However, with the advent of the digital age of communications, particularly with regards to social media and the advent of ‘Web 2.0’, things are beginning to change. We now have systems in place where not just experts, but anyone, can comment on and evaluate research at many stages of the research publication process.
Inspired by Martin Eve, I decided to make a documentation of academic-related stuff I’ve achieved in 2013. The last year was mostly occupado by the first year of my PhD, but other academic-ish stuff too as complimentary activities to research. This is kinda like a personal diary of ‘achievements’, as well as a documentation of the extent of work-procrastination. As such, please feel free not to share this with my supervisor 😉
Twitter is awesome. Users tweet over 340 million times a day, and the information load coming through it, and the speed at which it comes from the real world, makes it incredibly addictive as a social media or microblogging tool. In terms of the functions it offers though, how much is really understood? Everyone knows what tweeting, retweeting, and favouriting means on an anecdotal or personal level, but what about more generally. I set up a poll last week to gather data on what ‘favouriting’ a tweet means to different people. The results were pretty interesting, and make for a nice comparison with the results from another similar recent poll, on the ‘multiple personalities’ of the favourite function.
Here are the results from the data gathered on what motivates people to favourite tweets:
Results from 209 votes
The top 3 are pretty obvious:
The other poll had similar results, from 81 votes:
The author of the other post, Sherry Nouraini, suggests that this multiple-use signal is perhaps a flaw in Twitter’s design, based on uncertainty on the unity of its purpose, especially when it comes to community-building. I’d go one step further, and suggest that perhaps some innovative whizz kid out there can capitalise on this data (OK, it’s not an overwhelmingly huge data set) in some way to improve the services Twitter, or one of the multiple platforms it can run through, currently offers. Maybe. Feel free to keep voting on the poll btw, it would be interesting to see whether the pattern changes through time or with more data.
Bookmarking is the shining star of these li’l polls, both for future reference or to either tweet or read later on. I like the idea of it being used as a Facebook ‘like’, and wonder if those who voted for this are part of the ‘Facebook’ generation, as opposed to perhaps a more scholarly older generation who see beyond such a monotonous use. What do these data mean to you? I’m no social analyst, so it would be interesting to see what others think these patterns, and also discrepancies between data sets could possibly indicate.
For those who voted, here’s a pic of two dinosaurs having an apocalyptic bonk. You’ve earned it. No peaking if you didn’t vote.
Recently, Sherry Nouraini created an intriguing poll regarding the ‘multiple personalities’ of favouriting a tweet on Twitter. From a personal viewpoint, I use it similarly to the ‘Like’ function on Twitter, although anecdotal evidence combined with this poll suggest a wide variety of different uses. However, the sample size for this previous study was quite small, so it would be nice to a) see what happens if more people vote, and b) to have a comparative data set to see if the same trends are detected (I suspect the two of us are associated with different ‘internet crowds’).
So yeah, hopefully this poll below will work, and get a decent enough input so we can begin to see how favouriting is used as a social tool. You can select 3 choices, and I’ll post the results after a week or so (or longer if more people are getting involved). Some of the options do cross-over to various degrees, but I figured this captures pretty much the whole range of possibilities.
Thanks for voting! Please spread the word too – the more data the better any trend can be explained! 🙂
Green Tea and Velociraptors 