Collecting and Analyzing Public Data from Mastodon

Understanding online behaviors, communities, and trends through social media analytics is becoming increasingly important. Recent changes in the accessibility of platforms like Twitter have made Mastodon a valuable alternative for researchers. In this tutorial, we will explore methods for collecting and analyzing public data from Mastodon, a decentralized micro-blogging social network. Participants will learn about the architecture of Mastodon, techniques and best practices for data collection, and various analytical methods to derive insights from the collected data. This session aims to equip researchers with the skills necessary to harness the potential of Mastodon data in computational social science and social data science research.

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Publication Details

Published
2024-10-20
DOI
https://doi.org/10.1145/3627673.3679093
Citations
1
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
0.35
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article

Collecting and Analyzing Public Data from Mastodon

Gareth Tyson, Haris Bin Zia, Ignacio Castro
1 citations
Hate Speech and Cyberbullying Detection
0.35
article

Collecting and Analyzing Public Data from Mastodon

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

Abstract

Understanding online behaviors, communities, and trends through social media analytics is becoming increasingly important. Recent changes in the accessibility of platforms like Twitter have made Mastodon a valuable alternative for researchers. In this tutorial, we will explore methods for collecting and analyzing public data from Mastodon, a decentralized micro-blogging social network. Participants will learn about the architecture of Mastodon, techniques and best practices for data collection, and various analytical methods to derive insights from the collected data. This session aims to equip researchers with the skills necessary to harness the potential of Mastodon data in computational social science and social data science research.

Hong Kong University of Science and Technology (HK), University of Hong Kong (HK)
Openalex Percentile: Top 32%
Hate Speech and Cyberbullying Detection
0.35
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