Python: Collect Twitter follower network with twecoll

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Untuk mengumpulkan twitter follower dapat menggunakan Python script twecoll. Di samping itu juga menggunakan Gephi untuk memvisualisasikannya.

Langkah yang perlu di lakukan,

  • Get Twitter API keys
  • Download a customized version of the Python script twecoll
  • Configure the script
  • Run the script to collect the network and create the graph file


Prerequisites: Python and the command line

Untuk menjalankan twecoll, kita membutuhkan

  • python

Getting Twitter API keys

Kita perlu authentikasi dari twitter. Ini bisa dilakukan secara gratis & via web.


  • Go to apps.twitter.com
  • Create new app (top right)
  • Fill out Name, Description, Website (any valid URL is fine) and check the Developer Agreement after you have read it.
  • Switch to the ‘Keys and Access Tokens’ Tab.

Sidenote: Do not share these. People will abuse them. If you still do, like I did above, regenerate them to make the leaked version useless.

2. Download twecoll

Download twecoll,


3. Configure the script

Opsi FMAX yang perlu di ubah. FMAX mendefinisikan berapa banyak account yang mungkin kita kumpulkan datanya.

Untuk percobaan awal ada baiknya set FMAX kecil saja, misalnya 20.

Penggunaan twecoll

Jalankan 

python twecoll.py -h

Hasilnya 

usage: twecoll.py [-h] [-s] [-v]
                  {resolve,init,fetch,tweets,likes,edgelist} ...

Twitter Collection Tool

optional arguments:
  -h, --help            show this help message and exit
  -s, --stats           show Twitter throttling stats and exit
  -v, --version         show program's version number and exit  

sub-commands:
  {resolve,init,fetch,tweets,likes,edgelist}
    resolve             retrieve user_id for screen_name or vice versa
    init                retrieve friends data for screen_name
    fetch               retrieve friends of handles in .dat file
    tweets              retrieve tweets
    likes               retrieve likes
    edgelist            generate graph in GML format


4. Run twecoll to collect data

When the script runs for the first time, it will ask you for the consumer key and consumer secret. These are the two strings we got when we created the Twitter app. For future uses this isn’t necessary because twecoll saves the data in a file with the name .twecoll. If you want to start again, simply delete that file. If you use my modified version, it will be in the same directory, else it will be in the user directory.

We will use the script with the init, fetch and edgelist arguments.

First run

We need to cd to the location where we put the twecoll file. In my case I only need to enter cd twecoll because that’s the folder where I put the script. To run the script we need to tell the computer that Python should be used, then we say that the script should be run and finally we add the arguments for the script. For example 

python twecoll init luca

Because this is the first run we will be prompted to enter the consumer key and secret of our twitter app. The script will then generate an URL we need to open with a web browser, where we authorize the script to access our account. Twitter then gives us a PIN which we give the script. I then starts with the data collection.

Don’t use ctrl+c to copy in powershell. ctrl+c aborts the the running process in PowerShell. This is useful to stop the script at any time. But will make troubles when you want to copy the URL. You can either use the menu by clicking on the PowerShell symbol at the top left or you press enter to copy the highlighted text. If nothing is highlighted Enter will send the command you are writing at the moment. To paste text you can either use the menu or you simply click your right mouse button.

Authorizing twecoll with Twitter What you see when copying the URL to your browser. The PIN you get after authorizing twecoll in the browser.

You can use python twecoll -h to see all available commands. Use python twecoll COMMAND -h to get help for a certain command. You need to replace COMMAND with for example init. I will give you more information on the commands you will be using to collect Twitter networks. init command

This initalizes the data collection process. You need at least one argument to use it and that’s the screenname of the person you want to collect the network of: 

python twecoll init luca

Per default twecoll init will collect the list of people the account follows. If you want to look at the followers, you need to add the -o argument or --followers. It should look like this: 

python twecoll init luca -o

Or: 

python twecoll init luca --followers

The init command creates a file called SCREENNAME.dat with information about the accounts followed by or following the account you specified. It will also create a folder img, if doesn’t exist already, and put the avatars of the accounts it collects the data of there.

Once the init command finished collecting all accounts, it will write ‘Done.’.

fetch command

The fetch command goes through all the accounts collected by init and collects the IDs of the accounts followed by each of them. Again, we need to specify for which account we want to fetch the followings of their followings/followers.

In my example I would enter: 

python twecoll fetch luca

If it doesn’t exist, it creates a folder ‘fdat’ and for each account it collects the following IDs, it creates a file with the ID of the account followed by .f as the name. Inside it saves the IDs, one per line. Without additional information, because only those are relevant which exist in the .dat file.

The way fetch works makes it quite robust. If it stops for whatever reason (no internet, computer turned off, manually stopped) you can restart it with the same command and it will take up again where it stopped.

Sidenote: In the PowerShell/Terminal you can press the arrow keys to move through your command history.

If the .f file for a certain ID already exists, the script will skip that ID. This enables the pausing of data collection and helps when you create multiple networks where the same IDs are needed. But over time the files may be outdated. I recommend to delete the directory if you didn’t use the script for some time.

edgelist command

After we got all the necessary data, we need to combine it. We do that by using the edgelist command. Per default it creates a .gml file and tries to create a visualization with the Python package igraph. I don’t use igraph. If it isn’t installed, the script will skip this and print “Visualization skipped. No module named igraph”. This is fine. The .gml is still created.

I like to use the -m or --missing argument to include accounts where the script was unable to collect data on: python twecoll edgelist luca -m

If you use my modified version, you can use the -g or --gdf argument to create a .gdf file: 

python twecoll edgelist luca -g -m

The order of the arguments is irrelevant.

You now have eiter a SCREENNAME.gml or SCREENNAME.gdf file in the directory of the script, which you can open with Gephi or another tool that supports these formats.

I recommend my guide how to visualize Twitter networks with Gephi, which starts where you are now:

Guide: Analyzing Twitter Networks with Gephi 0.9.1

This is by no means a complete guide, but a starting point for people who want to analyze Twitter networks with Gephi. medium.com HTTPError 429: Waiting for 15m to resume

Welcome to the world of API limits. Twitter allows 15 API calls per 15 minutes per user per app. Read more on their API rate limits. The script waits for 15 minutes whenever twitter returns an error, that the limit is reached. Depending on the amount of followings/followers it can take several hours to days to collect all the data. Because of that I run the script on a Raspberry Pi 2 to not have to leave my computer running all the time.

Update: Thanks to a comment by Jonáš Jančařík, I was able to improve the twecoll code to collect the initial list of accounts with up to 100 fewer API calls. The modified version linked above already has the improvement. I created a pull request for the original version as well so it should be soon available to everyone.



Reference

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