Mastodoner: A Command-line Tool and Python Library for Public Data Collection from Mastodon

This paper introduces Mastodoner, a command-line tool and Python library aimed at simplifying access to public data on Mastodon, a prominent player in the Fediverse --- a decentralized network of interconnected social media platforms. Mastodoner addresses the challenges posed by Mastodon's decentralized nature by providing a unified interface for data collection, instance discovery, and secure data sharing. Through examples and demonstrations, this paper illustrates Mastodoner's capabilities in facilitating researchers' access to and analysis of public Mastodon data, thus advancing research in decentralized social media analytics. The tool and documentation are available at: https://github.com/harisbinzia/mastodoner.

Authors

Publication Details

Published
2024-10-20
DOI
https://doi.org/10.1145/3627673.3679217
Citations
3
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.75

Funders

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article

Mastodoner: A Command-line Tool and Python Library for Public Data Collection from Mastodon

Gareth Tyson, Haris Bin Zia, Ignacio Castro
3 citations
Data Visualization and Analytics
0.75
article

Mastodoner: A Command-line Tool and Python Library for Public Data Collection from Mastodon

Gareth Tyson, Haris Bin Zia, Ignacio Castro
article en
3 citations

Abstract

This paper introduces Mastodoner, a command-line tool and Python library aimed at simplifying access to public data on Mastodon, a prominent player in the Fediverse --- a decentralized network of interconnected social media platforms. Mastodoner addresses the challenges posed by Mastodon's decentralized nature by providing a unified interface for data collection, instance discovery, and secure data sharing. Through examples and demonstrations, this paper illustrates Mastodoner's capabilities in facilitating researchers' access to and analysis of public Mastodon data, thus advancing research in decentralized social media analytics. The tool and documentation are available at: https://github.com/harisbinzia/mastodoner.

Engineering and Physical Sciences Research Council
Openalex Percentile: Top 27%
Data Visualization and Analytics
0.75
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