Communities of scientists are emerging on Bluesky

Global network data: The ‘nicer’ alternative to X is fortifying its presence in fields that range from philosophy to chemistry, finance, and beyond.

We have extracted a new network of scientists and researchers, and a new global list of 100 science ‘influencers’ on the social media platform Bluesky.

And our numbers show that the community among scientists is getting stronger.

When my good colleague Lasse Hjorth Madsen and I extracted the Bluesky numbers in February, we found 8,900 influential scientists on the platform that were followed by at least 30 other scientists in the same network.

Distinct scientific communities can be clearly identified in the interactive visualization

Now there are 22,225 scientists that follow our definition – a 150 per cent increase.

The uptick in numbers could be either from an increase in Bluesky scientist numbers; from an increase in the number of scientists following other scientists there; or from both of these factors.

Network advantage

As a whole, Bluesky has shown only slow growth since February, with bursts of new users coming to the platform every time there is a new scandal by the owner of its larger competitor X (the former Twitter). It has 6 million users as of July 2024, a minute fraction compared to platforms like X and LinkedIn.

Scientists predominantly use X and LinkedIn for professional scientific networking, but with Bluesky and Mastodon in recent years hoping to break through as alternatives.

The fact that they are a small distinct community allows scientists to surveil and monitor their field, with less likelihood of their feeds being swamped by irrelevant posts

New social media platforms generally have a hard time competing against already consolidated incumbents.

The received wisdom is that older platforms like LinkedIn and X already have the user numbers and engagement. Users that join a newer platform therefore experience fewer meaningful conversations and activity, as there is less chance to meet people there initially that are closer to them socially, geographically, and in terms of common interest.

One community at a time

However, my claim is that it might not exactly work like that in the world of science.

Lasse and I have been working on mapping out researchers’ social media communities for several years now.

Scientists can gain an advantage from forming tight-knit communities of like-minded colleagues in specific fields. The fact that they are a small distinct community allows scientists to surveil and monitor their field, with less likelihood of their feeds being swamped by irrelevant posts.

And they are more likely to take the step to a smaller platform so long as a smaller community within their field already exists there.

To use a metaphor, scientists are like particles of dust at the beginning of our Solar System. As they ‘collide’ (or are introduced by colleagues to a new social platform within their field) they gradually form larger bodies like planets. These ‘planets’ are the communities that we now see.

This might be what is happening on Bluesky.

Our extraction of data shows a series of distinct communities. Within each of these communities the users tend to follow each other:

• Philosophy, psychology, cognitive science, ethics, science studies
• Authors and writers
• Ancient history, classics, archaeology
• Microbiology, genetics
• History
• Law and justice
• Ecology, nature and evolution
• Linguistics
• Military history
• Left wing and progressive politics
• Geoscience and palaeontology
• Chemistry
• Music theory
• Economy and Finance
• Plant biology

Top 100 scientist influencers

Our new global list of 100 science ‘influencers’ on Bluesky is here.

It uses a crafty method to find the most influential scientists, and you can get an overview here.

The method follows on from my annual TwiLi Index of recent years, which was an alternative measure of scientists’ ‘impact’, based on X and LinkedIn following numbers.

Click and have a look on Lasse’s interactive visualization here.

We have built our Bluesky networks by using an iterative algorithm that works like this: We start off with a list of hand-picked members of the scientific community. Then we expand the network step-by-step, finding the scientists on Bluesky that they follow, and subtracting those that are not followed by a substantial number from the existing network.

We then use a key term search to subtract those that do not have a bio description that indicates an affiliation with the scientific community. Then we repeat the process again and again, until we were not getting substantial numbers of new members.

As the recent breakup of the scientific social media exchange space has shown recently, an equilibrium where individual scientific fields ‘congeal’ together on different platforms is also possible.

The result? A science-oriented network of now 22,236 scientists on Bluesky. Most work in academia in research institutions. A few of them are science writers, independent researchers, or work at private organisations.

We compute centrality measures like ‘betweenness centrality’ and ‘PageRank’ to identify members that may be particularly influential.

Scientists could coalesce — or dissolve into fragments

What is going to happen from now on in terms of social media in science?

There are many potential pathways. There is a huge advantage for science if there is only one or two large platforms where all scientific exchange takes place, so long as scientists can use the platforms to monitor their fields without getting distracted. But as the recent breakup of the scientific social media exchange space has shown recently, an equilibrium where individual scientific fields ‘congeal’ together on different platforms is also possible.

I appreciate any comments or thoughts!

Does your department, faculty or university need to boost the international impact and career of your researchers? Here is more about my courses in social media for researchers. See other Mike Young Academy services here.