Home ›
Entities
› academia
› Characterizing twitter user topics and communication network dynamics of the “Liberate” movement during COVID-19 using unsupervised machine learning and social network analysis
Characterizing twitter user topics and communication network dynamics of the “Liberate” movement during COVID-19 using unsupervised machine learning and social network analysis
Research article (Online Social Networks and Media, 2020) · cited 65× · AI/ML
Characterizing twitter user topics and communication network dynamics of the “Liberate” movement during COVID-19 using unsupervised machine learning and social network analysis
Summary
Characterizing twitter user topics and communication network dynamics of the “Liberate” movement during COVID-19 using unsupervised machine learning and social network analysis is a scholarly article[1].
Key Facts
Characterizing twitter user topics and communication network dynamics of the “Liberate” movement during COVID-19 using unsupervised machine learning and social network analysis's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Characterizing twitter user topics and communication network dynamics of the “Liberate” movement during COVID-19 using unsupervised machine learning and social network analysis. Retrieved May 24, 2026, from https://4ort.xyz/entity/characterizing-twitter-user-topics-and-communication-network-dynamics-of-the-liberate-movement-during-covid-19-using-uns
MLA“Characterizing twitter user topics and communication network dynamics of the “Liberate” movement during COVID-19 using unsupervised machine learning and social network analysis.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/characterizing-twitter-user-topics-and-communication-network-dynamics-of-the-liberate-movement-during-covid-19-using-uns.
BibTeX@misc{4ortxyz_characterizing-twitter-user-topics-and-communication-network-dynamics-of-the-liberate-movement-during-covid-19-using-uns_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Characterizing twitter user topics and communication network dynamics of the “Liberate” movement during COVID-19 using unsupervised machine learning and social network analysis}}, year = {2026}, url = {https://4ort.xyz/entity/characterizing-twitter-user-topics-and-communication-network-dynamics-of-the-liberate-movement-during-covid-19-using-uns}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Characterizing twitter user topics and communication network dynamics of the “Liberate” movement during COVID-19 using unsupervised machine learning and social network analysis — https://4ort.xyz/entity/characterizing-twitter-user-topics-and-communication-network-dynamics-of-the-liberate-movement-during-covid-19-using-uns (retrieved 2026-05-24)
