How to Learn Programming – A Programmer’s Track Preview, Witchcraft Sourcing with Twitter and Ruby

I will be presenting at Sourcecon in Austin about sourcing using Bash, Ruby, Python, and R.

Here is how I look on a happy day. Feel free to say hi if you see me around. I am often friendly 🙂

You can also connect with me on Linkedin.

Check it out on Wednesday, September 27 • 2:25 pm – 3:00 pm under the Programmers track

This is a preview of witchcraft sourcing with Twitter and Ruby.

What you will learn from this awesome story:

How to create a CSV file from any Twitter list
The CSV file has valuable info about a user
Use the data for automating personalized DMs

This is a preview of what this CSV looks like.

Twitter has about 100 million tweets a day.

Those are a lot of tweets.

100 million.

Actually is about 250 million.

Or maybe more.

Just to make math easy. Let’s stick with 100 million tweets per day.

That’s like 1,000 tweets per second.

These numbers are hard to visualize in your mind.

But if you have used a social media tool like HootSuite you see how those tweets fly…

…at warp speed.

You cannot even read them. They appear on screen, they get pushed down your timeline and disappear fast.

So how do you keep up with so many tweets?

Drum roll…trrrrrrrr

Twitter lists!

But Twitter lists can be both your best friend and your worst enemy.

If you have a moderate number of users added to a Twitter list, then the tweets might not fly away as fast.

There is a good chance that you will be able to read your Twitter timeline using a Twitter list (with a social media tool).

Let’s say that a “moderate number” is 50 users.

You can easily scroll up and down a day’s worth of those 50 users.

What if your Twitter list has 500 users?

…feeling dizzy now.

What if it had 1,000 users?

…I need a bag…not feeling good.

So many users, so many tweets, so much data.

Why is Twitter data useful?

You can do sentiment analysis using Twitter.

Google this: “twitter sentiment analysis.”

You will get about 1 million results.

Sentiment analysis is used to find out if a piece of text is positive, negative or neutral.

Social media is all about emotions, right?

That’s why emoticons are such a big thing.

That’s why Facebook added emoticons to their “Like” button.

What if you could find the emotions from tweets. That would be awesome right?

What if you could find if someone is in a good mood. You contact them, and they reply back.

But what if they are in a bad mood. You contact them, and they block you.

It’s a gold mine to have that knowledge. Positive, negative or neutral.

We will leave sentiment analysis for another life. As this can become very technical.

1.21 Gigawatts. Great Scott!

What the heck is a gigawatt?

Yeah…that technical 🙂

For now, we are going to focus on getting data from Twitter. You have to start somewhere right?

Getting data from Twitter

Here is a summary for getting data from Twitter:

Install Ruby
Create a Twitter app
Find Twitter lists
Use magic potions to get Twitter data

0. Hardware

Let’s start with zero.

I previously used a MacBook Air, 2011, 4GB.

I also used a Mac mini, 2013, 16GB.

A cheap Thinkpad, 16GB with Ubuntu Linux. Then I moved to Fedora.

I have used Windows since Windows 98. OMG, I am feeling old right now.

I am a hardware geek.

What’s your favorite hardware?

Ideally, you are on Linux. Although there is a good chance, you are on Mac or Windows.

In Windows, it will be a little bit painful because you need a terminal to enter commands. And although Windows has one, it has different commands than Linux or OSX.

For Windows, I recommend that you install a Linux Virtual Machine. If you search on Youtube “install Linux VirtualBox on windows” you will find a lot of good tutorials to follow.