2021-10-08T14:36:23 n26261

Coordination Network Toolkit

Viewed: 736

A small Python command line tool and set of functions for studying coordination networks in Twitter and other social media data.

Rationale and Background

Social media activity doesn't occur in a vaccuum. Individuals on social media are often taking part in coordinated activities such as protest movements or interest-based communities.

Social media platforms are also used strategically to boost particular messages in line with political campaign goals or for commercial profit and scamming. This involves multiple accounts posting or reposting the same content, repeatedly and within a short time window (e.g. within 1 minute).

This software provides a toolkit to detect coordinated activity on social media and to generate networks that map the actors and their relationships. It provides a general purpose toolkit for multiple types of coordinated activity on any type of social media platform.

Firstly, it includes functionality for co-tweeting and co-retweeting (Keller et al., 2019; Schafer et al., 2017), where accounts post exactly the same text (co-tweets) or repost the same post within a short time window (co-retweets). Secondly, it includes functionality for co-link analysis, where multiple accounts post the same URLs repeatedly and in a short time window of each other (Giglietto et al., 2020). Thirdly, it adds two new types of network types: co-reply, where accounts are replying to the same post repeatedly together; and co-similarity, where accounts post similar text (but not exact duplicates), which relaxes the strict assumption of co-tweeting.

Five types of coordination networks supported:

1. Co-retweet: reposting the same post

2. Co-tweet: posting identical text

3. Co-similarity: posting similar text (Jaccard similarity or user-defined)

4. Co-link: posting the same link

5. Co-reply: replying to the same post

Installation and Requirements:

This tool requires a working Python 3.6 (or later) environment.

This tool can be installed from pip - this will handle installing the necessary dependencies.

pip install coordination_network_toolkit

Once you have installed it, you can use the toolkit in one of two ways:

1. As a command-line tool (run compute_networks --help to find out how)

2. As a Python library (import coordination_network_toolkit)

For more information, see the documentation.


Graham, Timothy, Bruns, Axel, Angus, Daniel, Hurcombe, Edward, & Hames, Sam (2021) #IStandWithDan versus #DictatorDan:the polarised dynamics of Twitter discussions about Victoria’s COVID-19 restrictions. Media International Australia, 179(1), pp. 127-148. https://eprints.qut.edu.au/207260/

Research areas

Pattern Recognition and Data Mining
Social media analysis
Similarity networks
Communication Technology and Digital Media Studies
Language, communication and culture
Studies in human society

Cite this collection

Graham, Timothy; QUT Digital Observatory; (2020): Coordination Network Toolkit. Queensland University of Technology. (Software) https://doi.org/10.25912/RDF_1632782596538

Related information

This is open source software, licensed under the MIT license. https://github.com/QUT-Digital-Observatory/coordination-network-toolkit/blob/main/LICENSE


MIT License


© Queensland University of Technology, 2021.

Data file types

Python code

Dates of development

From 2020-11-16 to 2020-12-18


Has association with
Timothy Graham  (Researcher)



Date record created:
Date record modified:
Record status:
Published - Open Access