Interesting to see the male/female ratio when it comes to people I follow and the people who follow me. My results are:
People I follow: men 74% women 24%
Followers: men 70% women 29%
The last year I have been interested in following other female founders (in tech) and I'm curious to see the results of others, especially of other women. The percentages give a good boost to continue to engage with other females on Twitter with the same interests.
Earlier this year I created a "personal CRM" using Airtable, collecting data about each person I follow on Twitter such as company, location, and gender using a virtual assistant. Curious, I reviewed the gender makeup and found that 79% of the people I follow (most of which work in tech) are men. I wrote about this discovery and have since sought to add more diversity to those I follow going forward.
This tool makes it far easier to get an estimation of this. I'd encourage everyone to give it a try and would love to see others report their findings in the comments here.
This is interesting. It'd be great to have something actionable on the other side once you analyze your account.
"Here's a twitter list of tech women" for instance
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Interesting how it estimates gender apparently quite accurately, either by pronouns in the bio or passing the first name to a gender guessing library.
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Love it! My results were pretty even for both people I follow and my followers.
People I follow: Nonbinary = 1% Men = 55% Women = 44%
My Followers: Nonbinary = 1% Men = 49% Women = 50%
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Love this application! Looks like a neat app to estimate gender demographic quick and act accordingly. Maker, thanks for making this!
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This is awesome, and I like seeing more tools/research pop-up on the theme "how skewed my filter bubble actually is" (here, in terms of gender, but there are also nifty things for political views, etc...).
It's too bad that this tool fell a bit short for me (and I don't actually blame the algo or the maker, given the data) :
People I follow : non-binary 1% (5), men 76% (328, no surprises there), women 23% (97, sad)...and "no gender, unknown 481".
I imagine those include brands/meme accounts/etc...but that still leaves the analysis unfinished given the numbers.
It's not like those 481 will find my redemption & suddenly restore the balance in the Force or anything (at least I wouldn't bet on it), but it would be great if the algo could try to categorize the brands/bots/memes together and give me the size of the real "uncategorized" population at least (so I get a sense of how representative the analysis above actually is).
Femwyse
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