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March 16, 2014 » 10:40 am

Gender Breakdown of my Twitter Stats

I just read Anil Dash’s excellent, thought-provoking piece, “The Year I Didn’t Retweet Men,” and it made me curious about my own Twitter behavior.

I used the tool that Anil mentioned, Twee-Q, and it reported that 83% of my retweets are of men. I was stunned to see that number, so I decided to investigate further.

First, I checked the gender breakdowns of whom I follow. Followerwonk reported 22% female, but also 33% undetermined. I only follow 191 people on Twitter, so I decided to do my own count. I first eliminated group accounts and bots, unless I knew there was a single person behind the group account, as with @WiserEarth (female) or @wikistrategies (male). That brought my following number down to 172.

Of the individual accounts I follow, 62% are male, 38% are female. This is better than what Followerwonk reported, but still not 50-50.

Also, based on this breakdown, I was still disproportionately amplifying the voices of men. However, I didn’t trust the 83% number. First, I didn’t trust that Twee-Q was accurately determining which voices were of which gender, especially given the discrepancy I saw with my Followerwonk numbers. Second, I didn’t think retweets alone were an accurate representation. I sometimes added my own commentary and used a citation rather than a retweet.

I decided to manually count all of my retweets and citations (not counting conversation, only amplification) in 2014. I’m not a prolific tweeter, so this was easily doable.

In 2014 so far, 74% of my retweets and 60% of my citations have been of men. In other words, 66% (two-thirds) of my retweets and citations are of men. The gender breakdown of whom I cite roughly maps to the breakdown of whom I follow, but I definitely retweet more men.

My initial reaction to these numbers was surprise, then rationalization. I won’t bother going into either — I don’t think they’re particularly important. The reality is that there are some well-documented implicit biases in society, and I’m statistically likely to suffer from all of them, no matter how enlightened I think I am.

The true measure of enlightenment is what you do with that self-awareness. I thought Anil’s metrics were interesting, but his followup experiment was inspiring. I’d like to try a similar experiment as a followup; I’m just not sure what that experiment should be. Any ideas?

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2 Responses to “Gender Breakdown of my Twitter Stats”

  1. I think (while a good exercise) it is important to think about why you re-tweet and the content you want to re-tweet. Then think about within the context of re-tweeting, would it be best served with more female voices. For example, if I like to re-tweet stories about race but I only re-tweet posts from Thomas Sowell but not someone like Robert Reich (a simple example), does this really serve the purpose of why I re-tweet?

  2. You're getting into the stuff I decided not to get into in my post. :-) I agree, you can't just make wholesale conclusions based on these numbers. You have to consider context, etc.

    I tweet about a lot of things, including tech, which is predominantly male. I feel like I know and follow a lot of great women in tech, and so my numbers might actually reflect favorably toward me.

    However, I also have a disproportionate percentage of female colleagues due to my work in the collaboration space. (Of the seven people at my previous company, I was the only man.) Not as many of them are as vocal online as I would like, but many of them are on Twitter at least.

    Again, you can't read too much into a simplified metric. If you did a content analysis of my blog, for example, I think you would find that I cite female colleagues far more often than male.

    I don't want to jump to any conclusions, but I'm certain I'm guilty of implicit biases, and — even accounting for all kinds of rationalization — I was still surprised by that 75% male retweet number. I'd love to play with an experiment in countering those biases, similar to what Anil did.

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