This article is co-authored with Dr. Livan Alonso Sarduy. The two charts below are based on a number of Twitter followers and their growth rate, after filtering out irrelevant or fake followers. Our next step is to identify top data science Twitter accounts, that are themselves followed by many other top data science Twitter accounts: in our opinion, this is one of the best metrics to measure real popularity.
For some, the number of Twitter followers is a must to make a real impact. Tweets that are re-tweeted can indirectly generate as much as 30% of the traffic a website can get. Here you can find the number of followers that some data science influencers are getting per day.
Note: Twitter users with <1k followers were excluded from both graphs
Here is a list of users that have >50k followers which do not appear in the graph (* two of them have lost followers)
Twitteruser Followers New Followers
Interesting: some data scientists with a high number of followers havea a slow follower growth. The following graph shows the relation between percentages of new followers/followers vs number of followers.
@drsanders and others do not appear in the graph because they have <1k followers
To attract more Twitter followers:
How was the data collected?