Rising stars: fastest growing tools on Twitter

To gain some insight in the popularity of online tools for scholarly communication, we have been tracking the number of Twitter followers monthly for each of the 600 tools in our growing database.

Twitter followers as a measure
The number of Twitter followers is one of many possible measures of interest/popularity, each with their own limitations (see for example, this blogpost by Bob Muenchen). Twitter follower data are freely available, allow for semi-automatic collection and are relatively transparent as accounts of followers can be checked. On the other hand, Twitter data have some limitations: only about 2/3 of the tools in our database have their own Twitter account, and following a tool’s tweets does not equal usage (in timing or volume). Also by definition it is restricted to people having Twitter accounts, which will favour younger generations and people more oriented to online communication. Finally, expression of interest by following happens at one moment in time so further rise or fall of a person’s interest in the tool is not reflected with this measure. Our global survey on research tool usage that is currently running, will provide more substantiated data on actual tool usage.

Given these limitations, we consider the number of Twitter followers to be an indication of potential interest in a tool. Looking over time, the rate of growth in Twitter followers can give an indication of tools that are most rapidly gaining interest.

Rising stars
The following tables show  the tools in our database with the largest relative increase in Twitter followers over the last six months (July 1, 2015-January 1, 2016), both for tools (n=207) that had over 1000 followers (Table 1) and tools (n=137) with between 100-1000 followers (Table  2) on July 1, 2015. We used these thresholds to filter out very early stages of Twitter accounts, that often see high growth rates with very low absolute numbers (e.g. a five-fold increase from 10-50)

Rank Tool / site Year of launch Research phase Twitter followers Jan 1, 2016 Twitter followers July 1, 2015 Relative increase
1 GitLab.com 2014 Publication 22.9K 12.9K 1.78
2 Jupyter 2015 Analysis 5519 3362 1.64
3 Open Library of Humanities 2014 Publication 4964 3102 1.60
4 Reddit Science 2008 Outreach 2183 1417 1.54
5 Qualtrics 2002 Analysis 11.7K 7634 1.53
6 BioRxiv 2013 Publication 3281 2235 1.47
7 Open Science Framework 2013 Preparation 4524 3127 1.45
8 Kaggle 2010 Preparation 42.3K 29.9K 1.41
9 Import.io 2013 Analysis 14.0K 10.0K 1.40
10 The Conversation 2011 Outreach 44.5K 33.3K 1.34

Table 1. Tools with the largest relative increase in Twitter followers – July 2015-January 2016 (> 1000 followers on July 1, 2015)

Rank Tool / site Year of launch Research phase Twitter followers Jan 1, 2016 Twitter followers July 1, 2015 Relative increase
1 Benchling 2013 Analysis 1419 689 2.06
2 Piirus 2014 Outreach 1877 915 2.05
3 Sciforum 2009 Outreach 242 120 2.02
4 Before the abstract 2014 Outreach 464 236 1.97
5 Mark2Cure 2014 Discovery 751 425 1.77
6 ManyLabs 2014 Analysis 196 111 1.77
7 SciVal 2009 Assessment 397 225 1.76
8 Elsevier Atlas 2014 Outreach 611 372 1.64
9 BookMetrix 2015 Assessment 286 175 1.63
10 Prolific Academic 2015 Analysis 783 490 1.60

Table 2. Tools with the largest relative increase  in Twitter followers – July 2015-January 2016 (100-1000 followers on July 1, 2015)

Some observations
The two groups of tools with fast-growing popularity on Twitter distinguished here likely represent different phenomena: established tools with continuously rising popularity and new tools that are fast gaining popularity. Assuming a more or less linear growth in Twitter followers, it will take longer to acquire (tens of ) thousands new followers than it will to gain a couple of hundred. This is reflected by the fact that the relative increase in Twitter followers is lower for the tools that had over 1000 followers in July  (Table 1) than for the tools that had between 100-1000 followers (Table 2). Similarly, the tools in Table 2 are somewhat more recent than those in Table 1.

Some notable exceptions are  Open Library of the Humanities and GitLab, which have quickly gained a very substantial following;  and Jupyter, which might have seen a lot of followers from @IPythonDev ‘transfer’ when IPython Notebooks continued as Project Jupyter. Not all ‘smaller’ tools are recent, too:  both SciForum and SciVal have been around for > 5 years but have only started out being active on Twitter recently. Also, SciVal may have been mainly interesting to university administrators at first, but has been made more accessible and interesting for ‘end user’ researchers.

Apparently, in scholarly communication tools do not go ‘viral’. Even for this group of fastest growers, the number of followers rarely doubles over the 6 month period.

Looking at the research phase the tools in the tables are aimed at, we predominantly see tools for Analysis, Publication and Outreach represented. For Analysis and Outreach, this might reflect the fact that potential users of these specific tools are relatively active on Twitter (perhaps more so than users of popular tools for e.g. Writing or Discovery). For Publication, it might also be a reflection of a growing interest in new publication models among various stakeholder groups in scholarly communication.

Of course, these are all post hoc explanations, that have not been tested, e.g. against a comparable set of tools with lower relative increase in Twitter followers, or substantiated by a more in-depth analysis, e.g. of the characteristics of people following these tools and sites on Twitter.

Tools per research activity
To further drill down into tools that are fast gaining popularity for specific research activities across the research cycle, the polar bar chart (Figure 1) below shows the tools with the highest relative increase in Twitter followers over the past six months (July 2015-January 2016) for each of 30 distinct research activities. Again, we focused on tools that had over 100 followers on July 1, 2015.

Twitter risers per research activity_jan2016_bottomlegend

Figure 1. Tools with the largest relative increase  in Twitter followers per research activity – July 2015-January 2016 (> 100 followers on July 1, 2015)

It is interesting to note that almost all tools in the polar bar graph are generic tools that can be used across the board of fields and disciplines. Of the 30 tools in this figure, only BioRxiv, DH Commons, OLH, Flypapers and Benchling are field specific. It’s too early to say that to see people flocking to your account you need to have a tool that can be used widely, but it is in line with a trend towards generic solutions. This could be something to dive further into once we have the tool usage data from our own survey.

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