Dissemination should be the other 50% of what authors do: being read and having impact will not happen by itself.
Authors can influence discovery and readership through owned media – i.e. their own communication activities.
Earned media – i.e. when influencers write about your work – is key to reaching larger and more diverse audiences.
There is plenty of data for tracking engagement
and use of articles, but it is scattered across multiple tools and
providers and can be misleading or even incorrect.
Listservs can have higher engagement than modern, ‘cool’, social networking tools.
INTRODUCTION
It takes much time and effort to write a paper – but how
much time and effort do authors put in to finding readers? In this case
study, I explain why I decided to devote an equivalent amount of time
and effort into finding and then engaging with my audience. Drawing on
available data for three papers I published in 2017, 2018, and 2019, I
describe how I promoted them, what happened, and what I learned. You
will learn about the Conversion Funnel and how tools like Kudos and
Altmetric can help drive and track your audience through its four
layers: awareness, interest, desire, and action (downloading and
reading). You will learn the difference between owned and earned media
and why finding influencers and riding waves can be so important. I also
identify areas inside the funnel where an author is dependent on
others, lacks control, or where data is missing, each of which makes
influencing the click‐through rate more difficult. The case study ends
with a set of 10 lessons learned.
WHY ACTION IS NEEDED
The urban legend that many academic papers go unread beyond their authors' ‘collegiate bubbles’ (Meho, 2007)
was seemingly validated in 2014 when the World Bank reported that a
third of its own papers were never downloaded (Doemeland & Trevio, 2014).
However, as with most urban legends, the data tells another story. The
World Bank's authors drew on data from a defunct repository and so
missed data from a new one which showed that all reports were downloaded
(C. Rossel, personal communication, May 2014). Ironically, the fuss
that greeted the World Bank paper certainly drove its readership beyond
its authors' bubble: it has been downloaded more than 8,000 times and,
as of 19 April 2019, has an Altmetric score that tops 200. However, an
essential question remains: how can authors boost their audience beyond
their immediate peer group?
Whilst a paywall might be a commonly cited barrier to being read (e.g. O'Brien, 2016),
others exist, such as arcane and foreign language, discoverability, and
even the comparative difficulty in using journals compared with other
media (Waller & Knight, 2012).
Plainly, you can only download what you know exists, so discoverability
must be a primary barrier, especially because paywalls are now
relatively easy to skirt with tools like Unpaywall (https://unpaywall.org/)
able to find free versions of many paywalled articles, and as a last
resort, there is what I like to refer to as the ‘Scottish Service’ (Note:
According to theatrical superstition, speaking the name of
Shakespeare's play Macbeth invites disaster, so thespians refer to it as
the Scottish Play and the lead character as the Scottish King. Rather
than invite disaster on our house, perhaps it would be safer to refer to
SciHub as the Scottish Service (https://en.wikipedia.org/wiki/The_Scottish_Play).) aka, SciHub.
Writing a paper is a significant investment in time (e.g. Margaryan, 2011),
and authors, their employers, and funders will want a return on this
effort. Of authors in the USA, 70% say they want readers beyond their
sub‐discipline, and just under half say they want to be read by
policymakers (Blankstein & Wolff‐Eisenberg, 2019).
So perhaps it is no surprise that some 300,000 scholars – around 10% of
researchers in developed economies (Organisation for Economic
Cooperation and Development[ OECD], 2019) – have created accounts on a tool, Kudos (www.growkudos.com),
which aims to help researchers communicate more effectively about their
work (C. Rapple, personal communication, May 2019). Since January 2018,
39% of those who have registered with Kudos have used its tools to
promote their articles, encouraged perhaps because using Kudos to
promote scholarly papers leads to more attention, and there is evidence
that downloads grow at a rate that is 23% faster than when it is not
used (Erdt, Aung, Aw, Rapple, & Theng, 2017).
However, these are early days, a recent review of using social media to
drive downloads and citations seems to show little effect on these
metrics (Davis, 2019) – but perhaps there are other objectives than simply boosting readership.
Take for example the University of Manchester. The university implements a protocol that uses Kudos, The Conversation (http://theconversation.com/global), and Altmetric (www.altmetric.com),
in addition to other University of Manchester services, to boost access
to its authors' articles and connect its researchers with policymakers
and influencers (UoMLibResearch, 2019).
I work at the OECD, an institution that helps governments
develop policies to improve the lives of their citizens. The help
primarily comes in the form of advice based on the research conducted by
the OECD at the behest of its funders. Plainly, if the OECD's research
findings and knowledge are left unread, the OECD would be failing in its
mission. This is why Angel Gurría, the OECD's Secretary‐General, often
reminds staff that ‘dissemination is the other 50% of what we do’. For
him, simply doing the research and sharing the results with governments
and funders is not enough; to fulfil its mission, the OECD needs to win
its fair share (or more!) of an ever‐larger audience's attention. This
is captured by the OECD's Publishing Policy in the form of a simple
objective: to ‘maximize dissemination’.
So, when I turned my hand to being an author, I thought I
would follow our Secretary‐General's injunction and spend as much time
promoting my articles as I had spent researching and writing them: to
see if I could maximize dissemination. This is my story of the ‘other
50% of being an author’, my story on trying to find readers beyond my
bubble.
HOW TO ENGAGE YOUR AUDIENCE
The other 50%: Preparation
Just as there are tools and techniques to make writing easier, so are there tools (e.g. Kudos, Altmetric, Plum Analytics (https://plumanalytics.com/), and various social media channels) and techniques (e.g. a conversion funnel) for boosting readership.
Kudos was developed to help researchers promote their
publications and track their efforts in doing so. It invites authors to
create a shareable summary ‘publications page’, where the work's core
messages are presented in a non‐technical way along with a link to the
original work on the publisher's website. (Kudos calls this a
‘publications page’, but I will refer to it as the article summary page
to distinguish it from the article landing page on the publisher's
website that hosts the actual publication.) It offers tools that enable
authors to create tagged links that can be embedded in ‘owned media’
messages and content (see Box 1
for definition). A dashboard gives daily reports on the number of times
the tagged links send traffic to the Kudos‐hosted article summary page,
so the success of each owned media effort can be assessed. The
dashboard also displays the publication's Altmetric ‘doughnut’, which
leads to its detailed Altmetric dashboard.
BOX 1. Owned, earned, and paid media
Owned media is when you post content on
communication channels that are under your control. These could be
websites, blogs, social media, or email.
Earned media is when other people (often known as
‘influencers’) are talking about your work on their websites, social
media, and other channels. It includes traditional or mainstream media
and things like letters to the editor, book reviews, and citations, as
well as word of mouth (e.g. mentions at conferences).
Paid media is when you pay to have your work
advertised in both traditional and online media. This would include
promoted items on social media channels and in search results.
Altmetric is a tool that enables researchers to track the reach and influence of their publications in ‘earned media’ (see Box 1),
specifically mainstream media, on social media, blogs and websites, in
reference management tools, Wikipedia, and in policy documents. Those
with access to its premium features can track citations in journals and
dig back through a publication's impact history. It works in almost real
time, so it gives an author the chance to join in online conversations
that they might otherwise have missed, for example, Twitter threads and
blog postings.
Using both tools together meant that I could track the
impact of my own promotion efforts and see where one of my papers was
being talked about by my audience. The latter was important in helping
me to engage with my readers, to discover and join in conversations with
people who had actually read my papers.
Funnelling conversions to drive readership
The Purchase Funnel (https://en.wikipedia.org/wiki/Purchase_funnel)
is a long‐established marketing principle. Originally coined in 1898 by
E. St. Elmo Lewis, it comprises four steps to making a sale: awareness,
interest, desire, and action. Being an analogue process, its lack of
reliable, affordable, data points brought about that oft‐quoted
marketer's quip about not knowing which half of one's advertising spend
is wasted (Bullmore, 2013).
The arrival of e‐commerce, with its extensive digital
exhaust, meant that the number of people clicking from one step to the
next could be tracked cheaply and easily, and the ‘conversion rate’ (the
percentage of people clicking from one funnel step to the next) could
be calculated. Access to these data has revolutionized marketing, and
any good marketer will now know the return on every advertising dollar
spent. However, as an online marketers' objective is not always a sale
(they might be after your vote), the digital funnel is known as the
Conversion Funnel (https://en.wikipedia.org/wiki/Conversion_funnel).
For an author in scholcom, the objective is to be read
(and, probably, cited), so this forms the lower, ‘action’, part of the
funnel. To get there, a reader must first be made aware that an article exists through search, owned, and earned media and have their interest stimulated by a summary page or abstract such that they desire to seek the full text and act by downloading and reading the work (Fig. 1).
Not everyone will pass right through the funnel; a percentage will be
lost at every step. So, maximizing dissemination requires boosting the
number being introduced at the top and, using traffic data, removing
frictions to reduce the drop‐out percentages at each step through the
funnel.
Conversion funnel – formally published journal article with summary page.
Source: Author's illustration.
Understanding and exploiting the Conversion Funnel is fundamental to any promotion strategy designed to boost readership:
Search is not just how findable your content
is to general search engines; it is dependent on the way your
publisher, and partners such as Kudos or ResearchGate, prepare and
present your content on and to academic discovery services (where a
majority of scholarly searches take place; Blankstein &
Wolff‐Eisenberg, 2019).
The best way authors can boost their chances of appearing in search
results is to post a variety of outputs (e.g. video, slides, blog posts)
with simple, engaging titles in addition to the formal work. Your
article's title should be clear and to the point, and all relevant
keywords should be woven into its abstract.
Owned media is in the hands of the author
(and potentially their employer, funder, or other partner) and should be
used in the long run to drive awareness among the author's own network.
This is where the author has the most leeway to act in the pursuit of
readers.
Earned media can be leveraged by asking
colleagues to send messages via their social media accounts but comes
into its own when ‘influencers’ choose to review, comment, react,
mention, and cite a published work and/or its author. Authors can seek
out influencers, especially those beyond their own bubble, for example
by sending out a press release.
A web page summarizing the article (ideally
presented in an accessible and non‐technical way) could be hosted on the
author's personal, departmental, and/or institution website; on the
author's page on collaboration networks like ResearchGate or LinkedIn;
and on the summary page of tools such as Kudos. To maximize
discoverability, an author would use all of these places. The objective
is to pique the interest of the visitor, to create the desire to go to
the publication's landing page on the publisher website.
The publication landing page will display
the title and abstract of the work, but it could also show key
illustrations and other elements of the work that encourage and
stimulate the visitor to act – to hit the download button. Authors have
little ability to act here because this page is usually under the
control of the publisher or repository owner.
The final, ‘action’, step is to download and read the work,
which could lead to further acts such as saving a publication's details
on reference and citation management tools such as Mendeley and,
looping back to ‘earned media’, citation and sharing among colleagues.
MY STORY
Round one: ‘We've failed’
My first article drew on data to show that the proportion
of born‐open journal articles had stalled at around 20%, leading me to
conclude that the dominant open access models, Gold and Green, had
failed, and therefore, a new approach was needed (Green, 2017a).
It was published in time for 2017s early autumn event season that
comprised ALPSP Conference, COASP, STM Annual Conference, and Open
Access Week. The timing was important because I wanted to use these
events not only to promote the article but to engage with its intended
audience: publishers and librarians.
On publication, I posted announcements on my Facebook
page (where, at the time, I had about 150 friends), Twitter (~600
followers), and LinkedIn (~400 connections). The result, 72
click‐throughs. I also posted an announcement to two Listservs,
generating 1,422 click‐throughs. Over the next 15 days, a period that
included both the ALPSP and the COASP Conferences, I made 12 more ‘owned
media’ promotional efforts: 10 using Twitter and 1 each on Facebook and
LinkedIn. Most of the earned media was on Twitter, where more than 500
different people tweeted about the paper (see Fig. 2).
This was an impressive volume, and many were researchers who exist
outside my bubble (publishers, their suppliers, and librarians).
Number of tweets per day 7–22nd September 2017. Weekends shaded in grey.
Source: Altmetric.
The launch day (L+0) spike tailed off on L+1, a Friday,
but picked up over the weekend and was sustained on L+5 and L+6 but then
tailed off as soon as the ALPSP Conference started. Was my audience
otherwise engaged and too busy to tweet? Or had the discussion exhausted
itself already? All I can report is that a majority of ALPSP attendees
that I spoke with had not heard of the paper, illustrating how hard it
is to gain the attention of one's target audience even with the help of
social media.
To my surprise, it all kicked off again on L+9 (Saturday
16th) with more than 100 tweets because an influencer, ‘mathgenius’,
posted the article title and a link on Hacker News (HN, https://news.ycombinator.com/item?id=15265507),
which in turn was featured on HN's front page, triggering an automatic
tweet to HN's 906 followers. This was re‐tweeted 30 times, including by
various other HN bots, one of which had >20,000 followers. Midway
through L+9, a tweet first posted on L+2 by Jon Tennent got a second
wind and, together with the HN audience, drove the ‘conversation’
through the weekend. A fair proportion of the tweets contained comments
or snippets from the article showing that the paper was being read, and
it was not just a bunch of bots chatting to each other.
The spike on L+13, midway through the COASP meeting, was
the result of my re‐tweeting an image that I found circulating that day
on Twitter (Fig. 3).
I linked the image to my article and, in an attempt to reach the COASP
audience (I did not attend the meeting), added the meeting's hashtag.
This tweet had 17,892 impressions, 42 re‐tweets, and 84 likes, and the
trackable link to the Kudos publication page was clicked 166 times.
Image I found on Twitter and re‐tweeted with a link to my article and hashtagged to COASP Conference.
In addition to all the action on Twitter, Altmetric
logged one blog post (Retraction Watch's Weekend Reads), seven mentions
on Facebook, 19 Google+ posts, and three Reddit posts – none of which,
apart from one on Facebook, were initiated by me. Incidentally, I am
only able to piece together this story of what happened thanks to the
earned media history captured and stored by Altmetric.
Over the next 8 months, I continued to promote the
article, mainly using Twitter, each time using a trackable link from
Kudos – each effort is shown with an ‘A’ in Fig. 4. After the launch month's high click‐through rate (CTR) (Table 1),
the CTR fluctuated, with the next highest being in January, 5 months
after publication. I also uploaded the Kudos‐created summary page in PDF
form onto ResearchGate, where it has been viewed 753 times.
Altmetric score since publication of ‘We've Failed’ article (Green 2017a).
Source: Kudos and Altmetric.
Table 1.
Efforts and click‐throughs
Month
Efforts
Click‐throughs
Click‐throughs per effort
September 2017
22
2,278
104
October 2017
9
222
25
November 2017
2
64
32
December 2017
2
4
2
January 2018
1
275
275
February 2018
4
220
55
March 2018
1
7
7
April 2018
3
33
11
May 2018
1
0
0
Source: Kudos.
It is all very well being able to see who has been
tweeting about my article and to get anecdotal feedback at conferences
and from the occasional personal email, but what I really wanted was to
know how often my article was being downloaded and by whom (or at least
know at which institutions my readers work or study). Knowing where and
by whom my article was being read would give me insight into where I
might be having an impact and, crucially, where I was not being heard.
As I had learned at the OECD, knowing this would help me learn more
about my actual readership and help me target future promotion efforts
to greater effect.
At OECD, we share download data with authors, and it
usually confirms prejudices and produces surprises in equal measure. For
example, I will not be breaking any confidences by revealing that
European Union and United Nations institutions have a healthy appetite
for OECD publications and datasets. But who would have thought that one
country's army officer training school cannot get enough of OECD's works
on education policy and the comparative performances of 15‐year‐olds at
school? This latter data point prompted our education department to
find out why resulting in an unknown unknown becoming a new connection.
So, download data are invaluable yet, as I was to discover, hard to get.
Even though Kudos is set up to integrate download data,
few publishers are able to export per‐article, per‐day usage data, and
unfortunately Wiley, Learned Publishing's publisher, was not one
of them. I had to request the data from the editor who obtained it from
the publisher to discover that, by the end of September 2017, the
article had been downloaded an astonishing 69,148 times. (This
counter‐compliant data point was double‐checked to ensure it had not
been distorted by bots.) In October, it was downloaded 1,834 times, in
November 967 times, and at an average of 315 times a month from then on
to the end of 2018. All I could get was the totals; I was unable to get
any data on which institutions or even which countries were reading my
article, and I had to wait until the middle of the next month to get
last month's data – hardly real time and no help when it came to
planning future promotion efforts.
Round two: ‘We're still failing’
A year later, I began to wonder if there had been any
progress to overcome the failure to deliver open access. A cursory
glance showed that nothing had changed: the needle showing the
proportion of born‐open articles had not moved, so I reached again for
my keyboard. This time, thinking on why the needle was stuck led me to
conclude that scholarly publishing was unaffordable whether done on an
open access or subscription basis. I suggested that lessons from digital
transformation be drawn upon to reduce costs and proposed a two‐step
process whereby scholars would first publish a preprint, and then,
providing the preprint gained attention, the author would be invited to
submit a paper for formal publication.
In order to be faithful to this proposition, I posted the
paper as a preprint on the Zenodo platform on 6th September 2018, once
again aiming for the autumn event season (Green, 2018).
In order to help readers funnel back to the original
paper (and in addition to the usual citation link in the references), I
added a tagged link in the preprint's abstract that would take readers
to the Kudos‐hosted summary page of the 2017 paper. By the end of April
2019, this link had been clicked 429 times, which is 8% of all visitors
to the preprint landing page.
Unfortunately, Zenodo's DOIs could not be integrated with
the Kudos platform, so I could not use it to promote the preprint.
However, Zenodo did integrate with Altmetric, so I can report on the
preprint's owned and earned Twitter coverage (Fig. 5).
Tweets per day for the preprint recorded by Altmetric.
Source: Altmetric (Note that the x‐axis scale is very different to Fig. 2.).
This time, I had to work harder to gain attention: 36 of
the 136 tweets (26%) over the launch period were mine (compared to 14 of
565 – 2.5% – the year before). My persistence was rewarded: for
example, my three tweets during the COASP meeting triggered 20
re‐tweets. However, at an average of 9 tweets per day, attention was
markedly down compared with the 35 tweets per day for the paper
published a year earlier: the influencer ‘mathgenius’ did not come to my
aid this time.
I did not keep a monthly record of the downloads
(displayed in real time on the Zenodo platform), but at the end of April
2019, the preprint had had 5,426 views and 1,796 downloads, and
recently, the count has been growing at about 300 and 150 per month,
respectively. However, as before, the download data have no detail: my
readers, their institutions, and their whereabouts remain unknown to me.
However, one of my objectives during this launch period
was to ask for comment and feedback on the preprint, so I could improve
the final paper. Within a month, I received substantive input from a
dozen individuals, including two who corrected errors: this I considered
to be a success.
Round three: Is open access affordable?
When I was writing the preprint, I was in contact with the editor of Learned Publishing,
Pippa Smart, where the first paper was published. As she was not put
off by the reaction to the preprint, I submitted a revised version to
the journal in October 2018. It went through the usual peer review and
acceptance process and was published on 25th January 2019 as part of a
special issue ‘Bring the Facts, Bust the Myths’ (Green, 2019a).
As with the preprint, I had to work hard to win attention
on Twitter, creating 29 out of the 146 tweets that mentioned the paper
(Fig. 6),
but with the launch period falling between two of the winter
conferences (APE 2019 was in mid‐January and R2R was in late‐February), I
was unable to generate much momentum after L+9 (2nd February).
Number of tweets per day for 25th January to 9th February 2019. Weekends shaded in grey.
Source: Altmetric.
Between January and May 2019, I promoted the paper on two
Listservs, generating 497 click‐throughs, LinkedIn (48) and
ResearchGate (14); tweeted 35 times (846); wrote two blog posts (88);
and commented on two other blog posts (48).
Downloads of my article for January to April totalled 4,015 (Fig. 7,
Article A). It is interesting to note that the ‘half‐life’ of my paper
seems a little longer than the other two most‐popular papers, but
Article D is unusual in building audience month by month.
Downloads (January to April 2019) per article for the first issue of Learned Publishing in 2019. My article is A. Note: The entire issue is free to download by anyone throughout 2019.
Source: Wiley/Learned Publishing.
Riding waves
One of the techniques I used to promote my articles is
called ‘Riding the wave’. Essentially, one keeps an eye open for events,
industry discussions, public statements, and social media conversations
with which one can engage and draw attention to a paper.
For example, in early 2017, Elsevier published a suggestion about how to work toward open access (Hersh, 2017),
which triggered a fair degree of comment on Listservs and the
Twittersphere. I posted a reply in the form of a blog post on Medium in
which I included a tagged link to my paper (Green, 2017b).
I then drew attention to the blog post using Twitter and LinkedIn,
attracting 1,400 reads from which there were 310 click‐throughs to the
Kudos‐hosted summary page – a click‐through response rate of 22%.
Another example was the invitation for formal responses to Plan S. I posted my response as a blog post (Green, 2019b)
and included tagged links to both papers' Kudos‐hosted summary pages. I
drew attention to the post through Twitter and LinkedIn, and this
effort resulted in 54 readers clicking through to the first paper's
summary page and 72 to the latter.
Most of my wave riding has been on Twitter where I use
one of two techniques: attract the attention of conference delegates by
using conference hashtags or join conversations by replying to suitable
tweets, in both cases using tagged links so I can track the result.
Five wave‐riding efforts that involved more than just ad hoc use of Twitter are summarized in Table 2.
Each effort contained messages from the paper, so even if readers did
not click through, a message was transmitted. It is interesting to note
that it is still possible to generate a worthwhile click‐through and
response rate many months post‐publication.
Table 2.
Summary of efforts (excluding individual tweets)
Timing
Context
Effort
Channel
Result
CT
RR
Paper 1
L+20
Elsevier proposition ‘working toward OA’
Reply to Elsevier
Medium
1,400 reads
310
22%
L+47
Invitation
Pushmi‐Pullyu
LSE Impact Blog
‘Most‐read listing’
67
n/a
L+143
J of Infomatics Board ‘mutinies’
Are mutinies effective?
Medium
610 reads
13
2%
L+153
Plan S Response deadline
My response to Plan S
Medium
611 reads
54
9%
Preprint
L+46
Invitation
Fail Fast
LSE Impact Blog
‘Most‐read listing’
?
n/a
Paper 2
L+2
J of Infomatics Board ‘mutinies’
Are mutinies effective?
Medium
610 reads
55
9%
L+15
Plan S Response deadline
My response to Plan S
Medium
611 reads
72
12%
L+96
BBC Radio 4 Programme on OA
Replies to 6 Tweets
Twitter
334 impressions
28
8%
Source: Kudos, Medium, and LSE Impact Blog.
Timing is days post‐launch. CT, click‐throughs to Kudos publication page; RR, response rate (CT/result).
DISCUSSION
Data everywhere but not a drop to drink
We know that our digital environment generates a firehose
of data. Yet, for authors in scholarly communications, data are hard to
come by. Unlike e‐commerce, where marketers create effective funnels
with vertically integrated digital platforms, a scholarly author has to
try and construct a Conversion Funnel from poorly‐ or unconnected
platforms and tools, many of which will not or cannot share their data
(see Fig. 8).
Conversion funnel showing data sources and availability.
Source: Author's illustration.
For my two formally published articles, I was able to
access data from my owned social media accounts and, thanks to
Altmetric, some earned media channels (e.g. Tweets written by other
people). Kudos could give me data about click‐through rates on my tagged
messages, traffic volumes to the summary page they host, and
click‐throughs to the publisher page.
For example, for the first paper, as I write this, Kudos
has logged 3,694 clicks from the 64 tagged promotion efforts I have made
via owned media channels, 6,299 views of the summary page hosted by
Kudos, and 878 clicks on the button that leads from that page to the
article's landing page on the publisher website. That latter step from
summary page to article landing page is a 14% click‐through rate – or to
put it another way, only 14% of summary page viewers were sufficiently
interested to have the desire to click through to the article.
However, this is where the data chain breaks: I have no
way of knowing how many of those who arrived on the article landing page
were actioned to download the paper. All I know is that more than
70,000 downloads have been recorded, but I am none the wiser about the
share that came from search and my own efforts or from earned media, nor
do I know anything about them, not even where they are located.
That the number of visitors to the Kudos‐hosted summary
page (6,299) exceeds the number of clicks on tagged links (3,694) shows
that the summary page is getting traffic from search and earned media –
but I do not know how much from either nor have access to any logfile
data that could help me understand more.
When it comes to citations, I get conflicting data. As I
write, Kudos tells me the first paper has nine ‘CrossRef citations’ yet
confusingly invites me to view them on Google Scholar, where I find a
list of 10 citing works above which is the metadata for my article and
the message ‘cited by 14’. Meanwhile, Altmetric shows eight citations
(sourcing the data from its sister company, Dimensions). The article
homepage on the publisher site shows seven citations. Confused? You will
be.
De‐duping these records to arrive at a clean,
comprehensive list of where my paper has been cited would not be easy –
none of the sites offers a data feed or downloadable file. Nor do any of
these tools offer alerts when new citations are found: for this, I have
to rely on services like ResearchGate (which, incidentally, reports 14
citations).
A simple data feed from Kudos and Altmetric would have
made it easier to create the charts in this paper – I had to type the
data into a spreadsheet. Altmetric's premium customers can download the
data for their publications, but you have to learn where the link is –
something I only discovered when doing a final edit for this article!
The data from Wiley arrived as a table in a word‐processing document and
I had to spend time copy–pasting into a spreadsheet before I could
chart it.
LICENCES AND REUSE: A CAUTIONARY TALE
As a favour, OECD once published a book for a
resource‐strapped fellow IGO. They insisted the work be published using a
CC‐BY licence. Six months post‐publication, the authors and IGO asked
OECD to issue a commercial distributor with a take‐down notice not
because the distributor was offering a version for sale but because it
was a crudely produced e‐book that, in their opinion, could damage their
reputation. The distributor had found the e‐book online and had
probably used some sort of automated process to strip the (copyrighted)
artist images from the cover and inside pages and re‐cast the work in a
new format: the result was anything but professional (a dog's breakfast
came to mind). To the frustration of the authors and IGO, I had to
explain that there was nothing to be done; the distributor had not
contravened any of the rules of a CC‐BY licence.
I tell this story because CC licences cut two ways when it
comes to boosting dissemination and impact. Yes, others may well expose
your work to audiences beyond your reach, but there are two issues to
consider.
First, there is the issue of reputation risk described
above. This can be mitigated by adding ND (non‐derivative) to a CC
licence, requiring disseminators to stick with your version of the work.
Second, and this is harder to overcome, unless you work
closely with your disseminators, you will have no idea who is re‐posting
your work, if your work has reached a larger audience, or – indeed – if
you are losing traffic and citations to alternative versions. In a
world where funders are demanding impact reports from their fundees,
getting access to all the download and citation data and knowing where
your work has made a mark is going to be more and more important. At
OECD, we encourage disseminators to use our shareable and embeddable
editions because they are trackable: we can see when they have been
embedded in websites and blogs and can monitor how often they are viewed
there, and we can offer users a route to the fully downloadable and
actionable editions on our website.
Working with partners to reach a broader audience is important, but keep an eye on your reputation and get the usage data.
LESSONS LEARNED
Be strategic. Find and use a toolkit that will create a Conversion Funnel to build awareness and draw users through the interest, desire, and action steps. If possible, aim to publish just ahead of a series of events at which the paper can be promoted. (Note:
I know that this will be a major challenge for most journals because
they have such long and unpredictable production times and lack tools to
plan releases. This is a major issue in journal publishing and one that
publishers should be working to fix!) Choose your redistributors with
care.
Be data‐driven. Log, measure, and track your
audience's progress through the Conversion Funnel. Measure your owned
media promotion efforts, so you can find out what works and what does
not.
Be reactive. Use tools that report results of
owned and earned media in real‐ or near‐real time. This will enable you
to shape future promotion efforts around what is working and to engage
with online conversations when they are happening. This is particularly
important on Twitter and other social media sites where discussions and
threads have short half‐lives.
Listservs rock. They might predate the internet, but postings to Listservs had a higher response rate than any other channel.
Reaching your target audience is hard: be active, be persistent.
Even if your target audience is well‐defined and easy to target,
winning their attention is hard because everyone is inundated with new
information every day. So, do not be afraid to keep on going on. To
avoid boredom and stimulate reaction, vary your message and tone. Use
illustrations. Be opportunistic: if you suddenly discover there is an
event going on, use the conference hashtag to follow it and jump in if
you get the chance; if there is a new industry debate catching your
target audience's attention, write a blog post (complete with tagged
links to the article) and draw attention to that. Be active: do not be
like one of the 80% on ResearchGate who just lurk (Khvatova &
Dushina, 2019).
Find influencers. As I found with the first
paper, someone influential can take your message to a wholly new
audience that is way beyond your own bubble. You might only have a
couple of hundred followers on Twitter, but you might know someone who
has a thousand or more. If you cannot approach them directly, wait until
they post something relevant and reply intelligently. If they have a
blog, watch what they write and then comment, with tagged links, when
you can. If your work might interest a broader public, do not hesitate
to contact journalists; earned mainstream media can reach way beyond
your own bubble and reach important audiences like policymakers and
concerned citizens.
Be creative. Do not post ‘read my article’
messages. Post snippets that inform, pique curiosity, or contribute to
debate. If possible, use illustrations that inform or entertain. Have a
clear call to action, such as inviting comment and feedback or that
leads to the next step in the Conversion Funnel.
Keep going. Unless your work is really out of
date, keep promoting it because there are always new audiences or new
contexts that make your work relevant, even months post‐publication.
Hassle your publisher for download data. Until
publishers make download data publicly accessible in real time,
regularly ask for it with as much detail as possible (where, when, who,
etc.).
It is less work than it seems. During the
2‐week launch period, I found I was scanning Twitter and other social
media channels perhaps four or five times a day (for a total of perhaps
30 min a day) and spending perhaps another 30 min creating new tweets
and replying/engaging with conversations on earned media. Afterwards, I
dialled back the effort to my normal scanning level with the occasional
burst of effort to write a blog post when needed. I am sure it never
amounted to the other 50% of my day – I'm sure I spent longer
researching and writing the original papers – but the results in terms
of readership and impact are, I am sure, better than if I had simply
published and passively left it to search engines to find my audience.
ACKNOWLEDGEMENTS
Each of the three articles cited in this case study are free
to download. I must thank ALPSP and Wiley, respectively owner and
publisher of Learned Publishing, and Zenodo, funded by CERN, for
publishing my articles on a free‐to‐read and download basis. I also
thank Kudos' Charlie Rapple for prompting me to write this paper.
Biography
T. Green
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T. Green
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