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How useful is twitter for academics, really?

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:

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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.

 

10 thoughts on “How useful is twitter for academics, really?

  1. Just to let you know, we can’t click to see stats on your tweets – that’s something only you can do.

    It would be cool if you could post pictures of the stats – this is a great post!

  2. I think an important unknown in this discussion is whether twitter clicks is all that matters? I have so far only had one really successful academic tweet, an advertisement for a paper. According to twitter, this tweet was seen 1894 times and had 65 engagements – 3,4%. So, very much in line with your statistic. However, if we go to its frontiers page, the paper actually enjoyed 324 views & downloads, in the time BEFORE it appeared on the journal frontpage. As twitter was the only place where we advertised for the paper, and bot-visits are not likely to be THAT massive, I must assume that the 65 engagements led to people sharing the paper through other channels, liberally.
    I think this supports your claim that for academics, getting the paper into the right hands is much more important than the naked conversion rate.

    • Totally agree Kaare, this is an important point. For one thing there is a lot left unanswered by raw clicks and engagement rates. I suspect academic reading and citing behaviors are pretty hard to predict in general from any one stat. A researcher may come across a paper tweet and favorite it but not click. Whether this relates to a future read and/or cite is totally unclear. I think this is why in the end I find the survey responses more informing than the raw conversion rates. It’s quite promising if more than half of academic twitter users claim to read papers found there with some regulatory. It at least goes against the notion that its all ’empty sharing’ – buzz on twitter does, somehow, equate to a higher chance that your audience finds and reads the paper. I think in the future almetrics will really need to find some kind of weighted measure that indexes different kinds of engagements and even somehow tracks eventual exposure – > citation conversion, if possible.

  3. Within the broader scope of things, I think tweeting a paper (and resulting exposure of paper) are only a subset of Twitter’s uses to an academic. For instance, I’ve found Twitter to be great for networking and have met many great people that I later met in-person at conferences, that I wouldn’t have known that well otherwise. Twitter can also be great for support, e.g., venting a bit after a not-so-positive review.

    More on topic, one paper I published earlier this year (first online: August 4, 2015) likely has gotten *much* more exposure due to Twitter than it otherwise would’ve gotten (paper: http://f1000research.com/articles/4-466/v1). As of today (Dec 4, 2015), the paper has 975 views and 210 downloads (according to F1000Research’s metrics on the paper’s page). Admittedly, I tweeted about the paper myself as soon as it was up, my reviewers (names publicly viewable) are all active on Twitter, and many have tweeted it since. According to Altmetrics, In the 4 months since the paper went up, 49 people have tweeted about the paper (http://f1000research.altmetric.com/details/4360925/twitter; n.b., altmetrics counts RTs as separate tweets). Perhaps this sort of information is more predictive of views/downloads than the click-through rates from individual tweets?

  4. Reblogged this on Oceanic Explorer and commented:
    Good post on how Twitter isn’t that effective in increasing readership of a journal article, though I think if a tweet does go viral, the conversion rate is bound to be lower than if 50 people actively engage with it. I would read at least the abstract of about %75 of the posts I retweet – otherwise, why bother retweeting it? To show an interest in the issue, that I can’t be bothered to read more about?
    I think the author of the original tweet and journal paper is also important – if it’s an author you have previously read and liked (or an organisation that you actively support), surely it’s more likely to encourage the click-through than just, well, a ‘clickbait’ title?
    Yep, maybe I’m deluded on that, which is why Buzzfeed and the like are so popular these days (21 Reasons Why Prawns Are Delicious) and true academic publication (The stochastic and comprehensively bland approach to garbage disposal literature) is not.

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