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Tweego

Generate second order ego networks for users from Twitter. Create egocentric graphs with the twitter api. Tweego allows you to resume data collection over multiple sessions.

Usage

Installation

pip install tweego

CLI

tweego [OPTIONS]

Options:
  -fo, --first-order            Flag: Collect first order ego
  -u, --users                   Flag: Collect user data
  -so, --second-order           Flag: Collect second order ego
  -g, --graph                   Flag: Generate graph file
  -d, --dir PATH                Directory to store data
  -k, --keys-file PATH          Location of the api keys JSON file
  -n, --screen-name TEXT        The screen name of the ego center user
  -f, --follower-limit INTEGER  Number of followers for the second order ego
  --version                     Show the version and exit.
  --help                        Show this message and exit.

Example

Collect everything:

tweego -d "dataset" -k "keys.json" -n "github" -fo -u -so -g

Collect first order connections only:

tweego -d "dataset" -k "keys.json" -n "github" -fo

Collect users and second order connections only:

tweego -d "dataset" -k "keys.json" -n "github" -u -so

API keys format

Tweego supports multiple api keys to speed up the data collection process. The api keys should be in a JSON file with the following format.

You can get these details from the Twitter developer website by creating a standalone app and then generating the keys and tokens.

[
    ...
    {
        "app_key": "<<app_key>>",
        "app_secret": "<<app_secret>>",
        "oauth_token": "<<oauth_token>>",
        "oauth_token_secret": "<<oauth_token_secret>>"
    },
    {
        "app_key": "<<app_key>>",
        "app_secret": "<<app_secret>>",
        "oauth_token": "<<oauth_token>>",
        "oauth_token_secret": "<<oauth_token_secret>>"
    },
    ...
]

Folder Structure

Once Tweego is done, the folder structure should look like this:

dir
├── users
│   ├── user_id_1.json
│   ├── user_id_2.json
│   └── ...
├── screen_name
│   ├── user_id_1
│   |   └── user_id_1.txt
│   ├── user_id_2
│   |   └── user_id_2.txt
│   └── ...
├── screen_name.txt
└── screen_name.gml

The users directory contains information about each user, the screen_name directory contains the follower ids of users. The screen_name.gml file contains the ego network and an application like Gephi can be used to analyze it.