Then, the chart title uses the words "registrations and subscriptions." If the blue dots on this chart also refer to blue-check accounts as in the first chart, then I fail to see how this chart conveys any information about registrations (wbich presumably would include free accounts). In that case, I am looking at accounts with 0 to 500 followers, pretty inconsequential accounts. I had presumed that the axis would be the same as in the first chart since there weren't any specific labels. This was before I noticed the inset in the first chart, easy to miss as it is tucked into the lower right corner. I was trying to figure out what is counted in the vertical axis. In the first chart, the story was described as "Elon Musk buys Twitter sparking waves of new users who later sign up for Twitter Blue". The second chart, which is an inset of the first, attempts to quantify the effect of the Musk acquisition on the number of "registrations and subscriptions". There might be one HBO fan account that quickly grew to 150,000 followers in just a few months but does the data label suggest to readers that HBO fan accounts as a group tend to quickly attain high number of followers? The designer arbitrarily labelled six specific accounts ("Crypto influencer", "HBO fan", etc.) but this feature risks sending readers the wrong message. ![]() (This is even more true if there is a survivorship bias - less successful accounts are more likely to be deleted over time.) Given the follower count is cumulative from the day of registration, we'd expect the accounts that started in the last few months should have markedly lower counts than those created years ago. Another sign that the top of the chart was removed is that an expected funnel effect is not seen. Surely, some of the celebrity accounts have way over 150,000 followers. That most Blue accounts have fewer than 5,000 followers? I also suspect that they chopped off the top of the chart (outliers) and forgot to mention it. Still, it's hard to know what the chart is saying. number of followers per year of existence) might be more informative. The chart has a built-in time bias since the longer an account exists, one would assume the higher the number of followers (assuming all else equal). The day of joining Twitter is not the day of becoming "Twitter Blue", almost surely not for any user (Nevetheless, the former is not a standard data element released by Twitter). The chart shows only Twitter Blue users so there is nothing to compare to. What's wrong with the data? It would seem the interesting question is whether blue checks are associated with number of followers. Those are very strange things to pair up on a scatter plot but I get it: the designer could only work with the data that can be pulled down from Twitter's API. The first chart is a scatter plot showing the day of joining Twitter and the total number of followers the account has as of early November, 2022. Anyone can get a blue check for US$8 per month. ![]() ![]() Yet another subscription service (but you're buying "freedom"!). Since Elon Musk acquired Twitter, he turned blue checks into a revenue generator. They are free but must be approved by Twitter. The New York Times printed several charts about Twitter "blue checks," and they aren't one of their best efforts ( link).īlue checks used to be credentials given to legitimate accounts, typically associated with media outlets, celebrities, brands, professors, etc.
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