Verdant Labs

Driven by data.

[Verdant Labs @verdantlabs]

How does your name relate to your occupation? https://t.co/FtvOl2V8mj

Per analysis of public data, the likelihood of a Penelope being an artist is roughly 20x the likelihood for an Erin.

[Verdant Labs @verdantlabs]

We've now launched https://t.co/zVuCOgChEq, which is a searchable database of prices people paid for local products and services. Check it out!

[Verdant Labs @verdantlabs]

@Cat9bx0219 Some amount of software engineering or possibly skill with analytical tools is probably necessary. For example, with significantly less work, a Wahington Post reporter was able to produce this analysis that’s less thorough but is interesting nonetheless: https://t.co/m2nWaGSdQ0

[Verdant Labs @verdantlabs]

@Cat9bx0219 That’s the data, but there was also a ton of work to process it (develop taxonomy grouping identical/similar professions, develop algorithm to de-dupe individuals, develop tools to parse and store the data, etc.). Hence we have no plans to dive back into it in the near future. :)

[Verdant Labs @verdantlabs]

@Cat9bx0219 https://t.co/CJm2k2m1hv

[Verdant Labs @verdantlabs]

@runnr_az Thanks - great to hear the positive Nametrix feedback!

[Verdant Labs @verdantlabs]

https://t.co/wiVaLgCp51 detects fake reviews. Here's what you find if you take a close look at review manipulation... #apps https://t.co/BEB3gg9m5u

[AppRecs @apprecscom]

For laughs: Travis Walter, One Busy App Reviewer https://t.co/ycrddTzvff
#fakereviews

[AppRecs @apprecscom]

Travis Walter, app reviewer extraordinaire https://t.co/ycrddTzvff

[AppRecs @apprecscom]

@kapeli FWIW, this is what review manipulation looks like: https://t.co/BfhzkWxngG Dash seems in the clear: https://t.co/qNf931M5CL

[Verdant Labs @verdantlabs]

You can now create a Favorites, Watchlist or other app list at https://t.co/wiVaLgCp51 https://t.co/k9ly6djKx2

[AppRecs @apprecscom]

Our Newest Feature: App Lists https://t.co/24n1uDphZ2

[Verdant Labs @verdantlabs]

@VTpollster @MorningEdition Just for fun - but interesting. Name predicts Congress' affiliations 2/3 of the time. https://t.co/EbMxdfHw9d

[Morning Edition @MorningEdition]

Most Dylans are Dems and most Duanes are Republicans -- at least acc to @verdantlabs analysis of contribution data: https://t.co/6CpG6SfhBw

[Ashley Westerman @_aswesterman]

We do a lot of serious stuff on @morningedition. So it's kinda great when I get to write stuff like this: https://t.co/fqVD4dPZB8 #eagles

[Morning Edition @MorningEdition]

Curtis is a Trump supporter. Mohammad is likely to vote for Clinton. And Karl? You guessed it... https://t.co/6CpG6SfhBw

[AppRecs @apprecscom]

Democratic vs. Republican Names https://t.co/uKQ5xT6vAi #names via @apprecscom

[AppRecs @apprecscom]

Positivity by Name - There's a link between first names and how positive people rate apps. https://t.co/5XRgrc0iZ1 #names via @apprecscom

[AppRecs @apprecscom]

The App Gender Gap - Women are major gamers, but the divide between "male" and "female" apps is widening. https://t.co/slTmyajCNY #apprecs

[AppRecs @apprecscom]

New post: Awesome New App Search Tools https://t.co/KIjhxJhiMv #apprecs #reviews #apps #iphone #ipad

[AppRecs @apprecscom]

#apprecs https://t.co/StVGcln117