2022 Law Prof Twittersphere

This year’s law prof twitter census results were recently published over on TheFacultyLounge. At the risk of being pilloried by law profs on twitter, I’ve again chosen to map out the prof following network and tabulate some rankings. As always, caveats abound (see below).

The Network

There was an impressive growth in the number of twitter users who follow law profs over the past couple of years. We’re now at 6,384,711 total unique twitter users that follow at least one law professor. That’s more a than 50% increase since I last did this a couple of years ago. We’ve also seen an increase in the degree to which law profs follow one another, with the law prof network density now reaching 0.094 (i.e. almost 10% of the possible connections within the law prof network are present).

The image below shows the network, clicking it should take you to an interactive version. Colors correspond to detected communities where ties are somewhat more likely amongst same-colored nodes than to users outside the community. I have again added a ‘link’ attribute to each node, which will take you to their Twitter profile. This makes it easier for you to follow (or unfollow?) users you find while exploring the network. Zooming in will reveal more node labels, so if you can’t find yourself use the search feature and then just do some zooming and panning.

Large network diagram showing different coloured groups of law professor twitter accounts, linked together by their following relationships.
The Law Prof Twittersphere of 2022 (click for interactive version, and give it some time to load)

Top-20 law profs by total followers:

HandleNameSchoolFollowers
tribelawLaurence TribeHarvard1379892
makaumutuaMakau MutuaBuffalo1292775
joycewhitevanceJoyce VanceAlabama982867
RWPUSARichard PainterMinnesota767632
lessigLawrence LessigHarvard346059
JonathanTurleyJonathan TurleyGeorge Washington328483
jentaubJennifer TaubWestern New England252386
AndrewBrandtAndrew BrandtVillanova224697
steve_vladeckSteve VladeckTexas203386
sandylocksKimberle CrenshawUCLA/Columbia190426
rgoodlawRyan GoodmanNYU172610
StevePeersSteve PeersEssex (UK)162221
ZephyrTeachoutZephyr TeachoutFordham142992
CassSunsteinCass SunsteinHarvard132407
orinkerrOrin KerrUSC119637
ProfMMurrayMelissa MurrayNYU101680
rickhasenRick HasenUC Irvine98887
mgeistMichael GeistOttawa93255
jacklgoldsmithJack GoldsmithHarvard89217
ScottJShapiroScott ShapiroYale86048

Top-20 law profs by law prof followers:

HandleNameSchoolProf Followers
orinkerrOrin KerrUSC920
AnthonyMKreisAnthony KreisGeorgia State682
steve_vladeckSteve VladeckTexas670
JillHasdayJill HasdayMinnesota666
DBRodriguez5Daniel B. RodriguezNorthwestern659
nancyleongNancy LeongDenver651
design_lawSarah BursteinOklahoma642
leahlitmanLeah LitmanUC Irvine597
daniellecitronDanielle CitronVirginia591
HoffProfDavid A. HoffmanPenn581
ProfMMurrayMelissa MurrayNYU579
brianlfryeBrian FryeKentucky576
lsolumLarry SolumGeorgetown576
ProfTolsonFranita TolsonUSC570
kalhanAnil KalhanDrexel557
OrlyLobelOrly LobelSan Diego534
kateashaw1Kate ShawCardozo525
PaulGowderPaul GowderNorthwestern516
EvidenceProfColin MillerSouth Carolina515
profbcrawfordBridget CrawfordPace504

Top-20 schools based on the number of law prof follower sums:

SchoolProf Followers
Virginia6050
Georgetown4232
NYU4125
UCLA4090
Ohio State3835
Fordham3816
Harvard3528
Chicago3380
UC Irvine3233
Northwestern3056
Cardozo3021
UNC2676
Emory2537
Colorado2526
Boston University2518
Yale2483
Michigan2430
Houston2420
Ottawa2287
Rutgers2273
George Washington2267

Bonus

This year’s bonus analysis:

I was curious about the almost 6.5 million twitter users who follow at least one law prof. Who are these people? Do they have a connection to a single prof or two that they follow? Or are they—for whatever reason—intensely interested in law prof tweets and thus following a whole bunch of law profs? To answer this, I tallied the number of law profs followed by each of these unique non-prof twitter users. It turns out the majority (72%) of twitter users who follow a law prof only follow a single one of the 1459 in the network.

That said, there are some real law prof enthusiasts on twitter. The distribution is highly skewed, so I’ve plotted it just for those who follow 50 or more law profs. As you can see, there are thousands (7,469) of such masochists. There is even a handful of users who follow more than 1000 law profs.

A figure showing the distribution of users by the number of law profs they follow on twitter. Highly skewed, with a maximum over 1000.
Caveat: I excluded known law profs from this analysis, but if the law prof was not included in the original census they could be counted amongst the enthusiasts here.

So, how do you attract attention from these non-law prof twitter users? The answer here is fairly simple: tweet. There’s certainly some more nuance you could add to this analysis, in that the substance of your tweets must matter at some level. Nonetheless, the relationship between tweeting and follower count is fairly clear:

Plot showing the two way relationship between logged tweets and logged followers. There is a positive almost linear relationship between the two.
Tweet more -> Get more followers

Caveats and data

As always, this process is imperfect. The census relies on self-reporting and is thus incomplete. If a user isn’t listed in the census they’re not in the network. Whenever I do this, people message me and ask me to add their handle. Unfortunately, I can’t add users to this version of the network because it just takes too much time. But, I do try to add these folks to the census next time round. I am forgetful though, so adding yourself to the census is an even more reliable way to be included.

As always, there were some handles in the census that threw errors of various types when trying to get their data via the Twitter API. Errors included: no such user, user suspended, or private profile. I removed isolates from the network, so if you don’t have any follower/following relationships with other law profs you won’t show up in the network data. I did very little data cleaning from the original census data, so if schools are represented with multiple names or there were typos in the input data those issues remain. Raw data available for download here, network data available on request.

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