Coordinated behavior is a relevant social media strategy employed for political astroturfing (Keller et al., 2020), the spread of inappropriate content online (Giglietto et al., 2020), and activism. Software for academic research and investigative journalism has been developed in the last few years to detect coordinated behavior, such as the CooRnet R package (Giglietto, Righetti, Rossi, 2020), which detects Coordinated Link Sharing Behavior (CLSB) and Coordinated Image Sharing on Facebook and Instagram (CooRnet website), and the Coordination Network Toolkit by Timothy Graham (Graham, QUT Digital Observatory, 2020).
The CooRTweet package builds on the existing literature on coordinated behavior and the experience of previous software, particularly CooRnet, to provide R users with an easy-to-use tool to detect various coordinated networks on Twitter and any other social media. It further opens up the possibility of cross-platform analysis.
install.packages("CooRTweet")The package is compatible with any data, provided that it is
formatted appropriately. It offers comprehensive support for data
obtained from the Twitter Academic API in the JSON format. This format
is generated by the function get_all_tweets from the R
package academictwitteR,
which simultaneously retrieves tweets and user information.
Additionally, the simple function prep_data aids in
formatting the data as required by the package.
prep_data() removes incomplete and duplicate shares by
default. Set drop_na = FALSE or
drop_duplicates = FALSE to retain them.
detect_groups() can select pairs within one inclusive
interval of time differences. For example,
time_window_low = 10, time_window = 30 includes pairs
shared exactly 10 or 30 seconds apart, as well as those between them.
The lower limit defaults to 0.
For a walk-through of the package, see the vignette source.
generate_coordinated_network() returns edges above the
median edge weight by default (subgraph = 1). Set
subgraph = 0 to return the full network with threshold
indicators on its edges.
The installed package includes
german_elections_sample, a 97,413-row anonymized temporal
excerpt for URL and image coordination examples. It is not
representative of the full campaign and cannot reproduce the paper’s
figures. Load it with
data("german_elections_sample", package = "CooRTweet").
The full anonymized dataset is not included in the installed
package. The same data previously distributed as
german_elections is now available only in the source
repository as data-raw/german_elections_full.rda.
From the root of a repository checkout, load it with:
load("data-raw/german_elections_full.rda") # creates german_electionsUse this full dataset with the paper
reproduction script. The script is kept in the source repository
under vignettes/, but is not included in the installed
package or built as a package vignette. Some plot panels require
non-public data and remain commented out in the public script.
Righetti, N., & Balluff, P. (2025). CooRTweet: A Generalized R Software for Coordinated Network Detection. Computational Communication Research, 7(1), 1. https://doi.org/10.5117/CCR2025.1.7.RIGH
Righetti, N., Kulichkina, A., Almeida Paroni, B., Cseri, Z. F., Aguirre, S. I., & Maikovska, K. (2025). Mainstreaming and transnationalization of anti-gender ideas through social media: the case of CitizenGO. Information, Communication & Society, 1-24.
Barrie, C., & Ho, J. C. T. (2021). academictwitteR: an R package to access the Twitter Academic Research Product Track v2 API endpoint. Journal of Open Source Software, 6(62), 3272, https://doi.org/10.21105/joss.03272
Giglietto, F., Righetti, N., & Rossi, L. (2020). CooRnet. detect coordinated link sharing behavior on social media. R package version 1.5.0. https://github.com/fabiogiglietto/CooRnet
Giglietto, F., Righetti, N., Rossi, L., & Marino, G. (2020). It takes a village to manipulate the media: coordinated link sharing behavior during 2018 and 2019 Italian elections. Information, Communication & Society, 23(6), 867-891. https://doi.org/10.1080/1369118X.2020.1739732
Graham, Timothy; QUT Digital Observatory; (2020): Coordination Network Toolkit. Queensland University of Technology. (Software) https://doi.org/10.25912/RDF_1632782596538
Keller, F. B., Schoch, D., Stier, S., & Yang, J. (2020). Political astroturfing on Twitter: How to coordinate a disinformation campaign. Political Communication, 37(2), 256-280. https://doi.org/10.1080/10584609.2019.1661888
Kulichkina, A., Righetti, N., & Waldherr, A. (2024). Protest and repression on social media: Pro-Navalny and pro-government mobilization dynamics and coordination patterns on Russian Twitter. New Media & Society, https://doi.org/10.1177/146144482412541.
Righetti, N., Giglietto, F., Kakavand, A. E., Kulichkina, A., Marino, G., & Terenzi, M. (2022). Political advertisement and coordinated behavior on social media in the lead-up to the 2021 German federal elections. Dusseldorf: Media Authority of North Rhine-Westphalia, 6. https://www.medienanstalt-nrw.de/fileadmin/user_upload/NeueWebsite_0120/Zum_Nachlesen/BTW22_Political_Advertisement.PDF
CooRTweet also powers the Coordinated Sharing Detection Service, a web-based service built on a streamlined version of the R package. It enables data journalists, fact-checkers, researchers, and other practitioners to analyze and visualize patterns of coordinated sharing in social media data.
This work was partially supported by the vera.ai project, funded by the European Union through the Horizon Europe program (Grant Agreement ID 101070093).