Tag: social media

How useful is twitter for academics, really?

Neuroconscience10 Comments

Recently I was intrigued by a post on twitter conversion rates (e.g. the likelihood that a view on your tweet results in a click on the link) by journalist Derek Thompson at the Atlantic. Derek writes that although using twitter gives him great joy, he’s not sure it results in the kinds of readership his employers would feel merits the time spent on the service. Derek found that even his most viral tweets only resulted in a conversion rate of about 3% – on par with the click-through rate of east asian display ads (i.e. quite poorly in the media world). Using the recently released twitter metrics, Derek found an average conversion of around 1.5% with the best posts hitting the 3% ceiling. Ultimately he concludes that twitter seems to be great at generating buzz within the twitter-sphere but performs poorly at translating that buzz into external influence.

This struck my curiosity, as it definitely reflected my own experience tweeting out papers and tracking the resultant clicks on the actual paper itself. However, the demands of academia are quite different than that of corporate media. In my experience ‘good’ posts do exactly result in a 2-3% conversion rate, or about 30 clicks on the DOI link for every 1000 views. A typical post I consider ‘successful’ will net about 5-8k views and thus 150-200 clicks. Below are some samples of my most ‘successful’ paper tweets this month, with screen grabs of the twitter analytics for each:

Screenshot 2015-12-04 11.42.45

Screenshot 2015-12-04 11.44.00

Screenshot 2015-12-04 11.44.41

Screenshot 2015-12-04 11.45.29

Sharing each of these papers resulted in a conversion rate of about 2%, roughly in line with Derek’s experience. These are all what I would consider ‘successful’ shares, at least for me, with > 100 engagements each. You can also see that in total, external engagement (i.e., clicking the link to the paper) is below that of ‘internal’ engagement (likes, RTs, expands etc). So it does appear that on the whole twitter shares may generate a lot of internal ‘buzz’ but not necessarily reach very far beyond twitter.

For a corporate sponsor, these conversion rates are unacceptable. But for academics, I would argue the ceiling of the actually interested audience is somewhere around 200 people, which corresponds pretty well with the average paper clicks generated by successful posts. Academics are so highly specialized that i’d wager citation success is really more about making sure your paper falls into the right hands, rather than that of people working in totally different areas. I’d suggest that even for landmark ‘high impact’ papers eventual success will still be predicted more by the adoption of your select core peer group (i.e. other scientists who study vegetarian dinosaur poop in the Himalayan range). In my anecdotal experience, I would say that I more regularly find papers that grab my interest on twitter than any other experience. Moreover, unlike ‘self finds’, it seems to me papers found on twitter are more likely to be outside my immediate wheelhouse – statistics publications, genetics, etc. This is an important, if difficult to quantify type of impact.

In general, we have  to ask what exactly is a 2-3% conversion rate worth? If 200 people click my paper link, are any of them actually reading it? To probe this a bit further I used twitters new survey tool, which recently added support for multiple options, to ask my followers about how often they read papers found on twitter:

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As you can see, out of 145 responses more than 50% in total said they read papers found on twitter “Occasionally” (52%) or “Frequently” (30%). If these numbers are at all representative, I think they are pretty reassuring for the academic twitter user. As many as ~45 out of ~150 respondents say they read papers on twitter “frequently” suggesting the service has become a major source for finding interesting papers, at least among its users. All together my take away is that while you shouldn’t expect to beat the general 3% curve, the ability to get your published work on the desks of as many as 50-100 members of your core audience is pretty powerful. This is a more tangible result than ‘engagements’ or conversion rates.

Finally, it’s worth noting that the picture on how this all relates to citation behavior is murky at best. A quick surf of the scientific literature on correlating citation rate and social media exposure is inconclusive at best. Two papers found by Neurocritic are examplars of my impression of this literature, with one claiming a large effect size and the other claiming none at all. In the end I suspect how useful twitter is for sharing research really depends on several factors including your field (e.g. probably more useful for machine learning than organic chemistry) and something i’d vaguely define as ‘network quality’. Ultimately I suspect the rule is quality of followers over quantity; if your end goal is to get your papers in the hands of a round 200 engaged readers (which twitter can do for you) then having a network that actually includes those people is probably worth more than being a ‘Kardashian’ of social media.

 

We the Kardashians are Democratizing Science

Neuroconscience8 Comments

I had a good laugh this weekend at a paper published to Genome Biology. Neil Hall, the author of the paper and well-established Liverpool biologist, writes that in the brave new era of social media, there “is a danger that this form of communication is gaining too high a value and that we are losing sight of key metrics of scientific value, such as citation indices.” Wow, what a punchline! According to Neil, we’re in danger of forgetting that tweets and blogposts are, according to him, the worthless gossip of academia. After all, who reads Nature and Science these days?? I know so many colleagues getting big grants and tenure track jobs just over their tweets! Never mind that Neil himself has about 11 papers published in Nature journals – or perhaps we are left to sympathize with the poor, untweeted author? Outside of bitter sarcasm, the article is a fun bit of satire, and I’d like to think charitably that it was aimed not only at ‘altmetrics’, but at the metric enterprise in general. Still, I agree totally with Kathryn Clancy that the joke fails insofar as it seems to be ‘punching down’ at those of us with less established CVs than Neil, who take to social media in order to network and advance our own fledgling research profiles. I think it also belies a critical misapprehension of how social media fits into the research ecosystem common among established scholars. This sentiment is expressed rather precisely by Neil when discussing his Kardashian index:

The Kardashian Index
The Kardashian Index

“In an age dominated by the cult of celebrity we, as scientists, need to protect ourselves from mindlessly lauding shallow popularity and take an informed and critical view of the value we place on the opinion of our peers. Social media makes it very easy for people to build a seemingly impressive persona by essentially ‘shouting louder’ than others. Having an opinion on something does not make one an expert.”

So there you have it. Twitter equals shallow popularity. Never mind the endless possibilities of having seamless networked interactions with peers from around the world. Never mind sharing the latest results, discussing them, and branching these interactions into blog posts that themselves evolve into papers. Forget entirely that without this infosphere of interaction, we’d be left totally at the whims of Impact Factor to find interesting papers among the thousands published daily. What it’s really all about is building a “seemingly impressive persona” by “shouting louder than others”. What then does constitute effective scientific output, Neil? The answer it seems – more high impact papers:

“I propose that all scientists calculate their own K-index on an annual basis and include it in their Twitter profile. Not only does this help others decide how much weight they should give to someone’s 140 character wisdom, it can also be an incentive – if your K-index gets above 5, then it’s time to get off Twitter and write those papers.”

Well then, I’m glad we covered that. I’m sure there were many scientists or scholars out there who amid the endless cycle of insane job pressure, publish or perish horse-racing, and blood feuding for grants thought, ‘gee I’d better just stop this publishing thing entirely and tweet instead’. And likewise, I’m sure every young scientist looks at ‘Kardashians’ and thinks, ‘hey I’d better suspend all critical thinking, forget all my training, and believe everything this person says’. I hope you can feel me rolling my eyes.  Seriously though – this represents a fundamental and common misunderstanding of the point of all this faffing about on the internet. Followers, impact, and notoriety are all poorly understood side-effects of this process; they are neither the means nor goal. And never mind those less concrete (and misleading) contributions like freely shared code, data, or thoughts – the point here is to blather and gossip!

While a (sorta) funny joke, it is this point that is done the most disservice by Neil’s article. We (the Kardashians) are democratizing science. We are filtering the literally unending deluge of papers to try and find the most outrageous, the most interesting, and the most forgotten, so that they can see the light of day beyond wherever they were published and forgotten. We seek these papers to generate discussion and to garner attention where it is needed most. We are the academy’s newest, first line of defense, contextualizing results when the media runs wild with them. We tweet often because there is a lot to tweet, and we gain followers because the things we tweet are interesting. And we do all of this without the comfort of a lofty CV or high impact track record, with little concrete assurance that it will even benefit us, all while still trying to produce the standard signs of success. And it may not seem like it now – but in time it will be clear that what we do is just as much a part of the scientific process as those lofty Nature papers. Are we perfect? No. Do we sometimes fall victim to sensationalism or crowd mentality? Of course – we are only fallible human beings, trying to find and create utility within a new frontier. We may not be the filter science deserves – but we are the one it needs. Wear your Kardshian index with pride.

Short post: why I share (and share often)

Neuroconscience1 Comment

If you follow my social media activities I am sure by now that you know me as a compulsive share-addict. Over the past four years I have gradually increased both the amount of incoming and outgoing information I attempt to integrate on a daily basis. I start every day with a now routine ritual of scanning new publications from 60+ journals and blogs using my firehose RSS feed, as well as integrating new links from various Science sub-reddits, my curated twitter cogneuro list, my friends and colleagues on Facebook, and email lists. I then in turn curate the best, most relevant to my interests, or in some cases the most outrageous of these links and share them back to twitter, facebook, reddit, and colleagues.

Of course in doing so, a frequent response from (particularly more senior) colleagues is: why?! Why do I choose to spend the time to both take in all that information and to share it back to the world? The answer is quite simple- in sharing this stuff I get critical feedback from an ever-growing network of peers and collaborators. I can’t even count the number of times someone has pointed out something (for better or worse) that I would have otherwise missed in an article or idea. That’s right, I share it so I can see what you think of it!  In this way I have been able to not only stay up to date with the latest research and concepts, but to receive constant invaluable feedback from all of you lovely brains :). In some sense I literally distribute my cognition throughout my network – thanks for the extra neurons!

From the beginning, I have been able not only to assess the impact of this stuff, but also gain deeper and more varied insights into its meaning. When I began my PhD I had the moderate statistical training of a BSc in psychology with little direct knowledge of neuroimaging methods or theory. Frankly it was bewildering. Just figuring out which methods to pay attention to, or what problems to look out for, was a headache-inducing nightmare. But I had to start somewhere and so I started by sharing, and sharing often. As a result almost every day I get amazing feedback pointing out critical insights or flaws in the things I share that I would have otherwise missed. In this way the entire world has become my interactive classroom! It is difficult to overstate the degree to which this interaction has enriched my abilities as a scientists and thinker.

It is only natural however for more senior investigators to worry about how much time one might spend on all this. I admit in the early days of my PhD I may have spent a bit too long lingering amongst the RSS trees and twitter swarms. But then again, it is difficult to place a price on the knowledge and know-how I garnered in this process (not to mention the invaluable social capital generated in building such a network!). I am a firm believer in “power procrastination”, which is just the process of regularly switching from more difficult but higher priority to more interesting but lower priority tasks. I believe that by spending my downtime taking in and sharing information, I’m letting my ‘default mode’ take a much needed rest, while still feeding it with inputs that will actually make the hard tasks easier.

In all, on a good day I’d say I spend about 20 minutes each morning taking in inputs and another 20 minutes throughout the day sharing them. Of course some days (looking at you Fridays) I don’t always adhere to that and there are those times when I have to ‘just say no’ and wait until the evening to get into that workflow. Productivity apps like Pomodoro have helped make sure I respect the balance when particularly difficult tasks arise. All in all however, the time I spend sharing is paid back tenfold in new knowledge and deeper understanding.

Really I should be thanking all of you, the invaluable peers, friends, colleagues, followers, and readers who give me the feedback that is so totally essential to my cognitive evolution. So long as you keep reading- I’ll keep sharing! Thanks!!

Notes: I haven’t even touched on the value of blogging and post-publication peer review, which of course sums with the benefits mentioned here, but also has vastly improved my writing and comprehension skills! But that’s a topic for another post!

( don’t worry, the skim-share cycle is no replacement for deep individual learning, which I also spend plenty of time doing!)

“you are a von economo neuron!” – Francesca 🙂

Fun fact – I read the excellent scifi novel Accelerando just prior to beginning my PhD. In the novel the main character is an info-addict who integrates so much information he gains a “5 second” prescience on events as they unfold. He then shares these insights for free with anyone who wants them, generating billion dollar companies (of which he owns no part in) and gradually manipulating global events to bring about a technological singularity. I guess you could say I found this to be a pretty neat character 🙂 In a serious vein though, I am a firm believer in free and open science, self-publication, and sharing-based economies. Information deserves to be free!

Snorkeling ’the shallows’: what’s the cognitive trade-off in internet behavior?

Neuroconscience12 Comments

I am quite eager to comment on the recent explosion of e-commentary regarding Nicolas Carr’s new book. Bloggers have already done an excellent job summarizing the response to Carr’s argument. Further, Clay Shirky and Jonah Lehrer have both argued convincingly that there’s not much new about this sort of reasoning. I’ve also argued along these lines, using the example of language itself as a radical departure from pre-linguistic living. Did our predecessors worry about their brains as they learned to represent the world with odd noises and symbols?

Surely they did not. And yet we can also be sure that the brain underwent a massive revolution following the acquisition of language. Chomsky’s linguistics would of course obscure this fact, preferring us to believe that our linguistic abilities are the amalgation of things we already possessed: vision, problem solving, auditory and acoustic control. I’m not going to spend too much time arguing against the modularist view of cognition however; chances are if you are here reading this, you are already pretty convinced that the brain changes in response to cultural adaptations.

It is worth sketching out a stock Chomskyian response however. Strict nativists, like Chomsky, hold that our language abilities are the product of an innate grammar module. Although typically agnostic about the exact source of this module (it could have been a genetic mutation for example), nativists argue that plasticity of the brain has no potential other than slightly enhancing or decreasing our existing abilities. You get a language module, a cognition module, and so on, and you don’t have much choice as to how you use that schema or what it does. The development of anguage on this view wasn’t something radically new that changed the brain of its users but rather a novel adaptation of things we already and still have.

To drive home the point, it’s not suprising that notable nativist Stephen Pinker is quoted as simply not buying the ‘changing our brains’ hypothesis:

“As someone who believes both in human nature and in timeless standards of logic and evidence, I’m skeptical of the common claim that the Internet is changing the way we think. Electronic media aren’t going to revamp the brain’s mechanisms of information processing, nor will they supersede modus ponens or Bayes’ theorem. Claims that the Internet is changing human thought are propelled by a number of forces: the pressure on pundits to announce that this or that “changes everything”; a superficial conception of what “thinking” is that conflates content with process; the neophobic mindset that “if young people do something that I don’t do, the culture is declining.” But I don’t think the claims stand up to scrutiny.”

Pinker makes some good points- I agree that a lot of hype is driven by the kinds of thinking he mentions. Yet, I do not at all agree that electronic media cannot and will not revamp our mechanisms for information processing. In contrast to the nativist account, I think we’ve better reason than ever to suspect that the relation between brain and cognition is not 1:1 but rather dynamic, evolving with us as we develop new tools that stimulate our brains in unique and interesting ways.

The development of language massively altered the functioning of our brain. Given the ability to represent the world externally, we no longer needed to rely on perceptual mechanisms in the same way. Our ability to discriminate amongst various types of plant, or sounds, is clearly sub-par to that of our non-linguistic brethren. And so we come full circle. The things we do change our brains. And it is the case that our brains are incredibly economical. We know for example that only hours after limb amputation, our somatosensory neurons invade the dormant cells, reassigning them rather than letting them die off. The brain is quite massively plastic- Nicolas Carr certainly gets that much right.

Perhaps the best way to approach this question is with an excerpt from social media. I recently asked of my fellow tweeps,

To which an astute follower replied:

Now, I do realize that this is really the central question in the ‘shallows’ debate. Moving from the basic fact that our brains are quite plastic, we all readily accept that we’re becoming the subject of some very intense stimulation. Most social media, or general internet users, shift rapidly from task to task, tweet to tweet. In my own work flow, I may open dozens and dozens of tabs, searching for that one paper or quote that can propel me to a new insight. Sometimes I get confused and forget what I was doing. Yet none of this interferes at all with my ‘deep thinking’. Eventually I go home and read a fantastic sci-fi book like Snowcrash. My imagination of the book is just as good as ever; and I can’t wait to get online and start discussing it. So where is the trade-off?

So there must be a trade-off, right? Tape a kitten’s eyes shut and its visual cortex is re-assigned to other sensory modalities. The brain is a nasty economist, and if we’re stimulating one new thing we must be losing something old. Yet what did we lose with language? Perhaps we lost some vestigial abilities to sense and smell. Yet we gained the power of the sonnet, the persuasion of rhetoric, the imagination of narrative, the ability to travel to the moon and murder the earth.

In the end, I’m just not sure it’s the right kind of stimulation. We’re not going to lose our ability to read in fact, I think I can make an extremely tight argument against the specific hypothesis that the internet robs us of our ability to deep-think. Deep thinking is itself a controversial topic. What exactly do we mean by it? Am I deep thinking if I spend all day shifting between 9 million tasks? Nicolas Carr says no, but how can he be sure those 9 million tasks are not converging around a central creative point?

I believe, contrary to Carr, that internet and social media surfing is a unique form of self stimulation and expression. By interacting together in the millions through networks like twitter and facebook, we’re building a cognitive apparatus that, like language, does not function entirely within the brain. By increasing access to information and the customizability of that access, we’re ensuring that millions of users have access to all kinds of thought-provoking information. In his book, Carr says things like ‘on the internet, there’s no time for deep thought. it’s go go go’. But that is only one particular usage pattern, and it ignores ample research suggesting that posts online may in fact be more reflective and honest than in-person utterances (I promise, I am going to do a lit review post soon!)

Today’s internet user doesn’t have to conform to whatever Carr thinks is the right kind of deep-thought. Rather, we can ‘skim the shallows’ of twitter and facebook for impressions, interactions, and opinions. When I read a researcher, I no longer have to spend years attending conferences to get a personal feel for them. I can instead look at their wikipedia, read the discussion page, see what’s being said on twitter. In short, skimming the shallows makes me better able to choose the topics I want to investigate deeply, and lets me learn about them in whatever temporal pattern I like. Youtube with a side of wikipedia and blog posts? Yes please. It’s a multi-modal whole brain experience that isn’t likely to conform to ‘on/off’ dichotomies. Sure, something may be sacrificed, but it may not be. It might be that digital technology has enough of the old (language, vision, motivation) plus enough of the new that it just might constitute or bring about radically new forms of cognition. These will undoubtably change or cognitive style, perhaps obsoleting Pinker’s Bayesian mechanisms in favor of new digitally referential ones.

So I don’t have an answer for you yet ToddStark. I do know however, that we’re going to have to take a long hard look at the research review by Carr. Further, it seems quite clear that there can be no one-sided view of digital media. It’s not anymore intrinsically good or bad than language. Language can be used to destroy nations just as it can tell a little girl a thoughtful bed time story. If we’re to quick to make up our minds about what internet-cognition is doing to our plastic little brains, we might miss the forest for the trees. The digital media revolution gives us the chance to learn just what happens in the brain when its’ got a shiny new tool. We don’t know the exact nature of the stimulation, and finding out is going to require a look at all the evidence, for and against. Further, it’s a gross oversimplification to talk about internet behavior as ‘shallow’ or ‘deep’. Research on usage and usability tells us this; there are many ways to use the internet, and some of them probably get us thinking much deeper than others.