Tell me who your followers are and I tell you who you are.
You have lots of followers, congrats! You're popular, maybe an influencer. But, do you actually know who's following you?
If you have thousands of followers, that could be a tricky question to answer. Let's use Machine Learning to try to answer that question.
MonkeyLearn's Twitter account as today (Oct 4th, 2016), has almost 20,000 followers. It would be great to know which kind of people follow us, find out more about their interests, who they are, what they do, and try to figure out why they follow us. That could give us useful insights about our user base and product.
We quickly used Twitter's public API to download the bios of all of our followers. You can take a look at the Python script here. In order to use it, you'll need to get your API tokens.
We stored all the data in a simple CSV file. First column: user handle, second column: user bio. Like this:
Then we wrote a simple Python command to read and concatenate all the bios of our users into a text variable and send it to our Keyword Extractor model in MonkeyLearn.
You can execute the command like this:
python keywords_csv.py -s 4000 -c 1 -k 100 -t <<YOUR TOKEN HERE>> followers_bios.csv
-s option sets the max number of rows (bios) to use. I suggest to limit to the last 4,000 texts, too much of them would take a lot of time to process.
-c option sets the column number (starting on 0) where the bios are located in the CSV file.
-k option sets the max number of keywords to return.
-t option sets your MonkeyLearn API token.
And lastly, the followers_bios.csv is the CSV file where you stored the bios.
The keywords returned will be sorted according to their relevance within the texts.
You can even try to do the same process just copying and pasting the texts within MonkeyLearn's GUI, just go to the API section. This will limit just to the top 10 keywords.
And the results for the top 100 keywords associated with MonkeyLearn's followers are:
That's great! Definitively what we wanted to see, but we also found some interesting insights:
Strong popularity within Developers, we have keywords like Developer, Web Developer, Software Developer, Engineer, App Developer, Programmer, Game developer, Mobile App Developer, Software Engineer, Data Scientist, Mobile Developer, Coder.
Strong popularity within people in the Data Science and Technology space: Machine Learning, Big Data, Data Science, Data, Analytics, Technology, Artificial Intelligence, Research, Innovation, Science, Natural Language Processing, Programming.
Some Other Titles arose, which are very interesting besides the Developer and Data Scientist, all of them very related to the startup world: Designer, Entrepreneur, Consultant, Manager, Founder, Blogger, Business Developer, Photographer, Student, CTO, Product Manager, Scientist, Speaker, CEO, Analyst, Project Manager, Writer, Author.
Non-tech disciplines which have been growing a lot in our community and we plan to give more tools: Marketing, Startups, Social Media, Business, Graphic Design, Digital Marketing, Music, Market Research, Business Intelligence, SEO.
Personal characteristics which clearly denote that we have very enthusiastic and geeky followers: enthusiast, geek, lover, music lover, love, fan, life, passion, creator, father, expert.
Hope you enjoyed this quick post, I'd love to know your own insights with your followers!
October 4th, 2016