H-TFIDF: What makes areas specific over time in the massive flow of tweets related to the covid pandemic?

Rémy Decoupes, Rodrique Kafando, Mathieu Roche, Maguelonne Teisseire

Open source

DOI: 10.5194/agile-giss-2-2-2021
Published: 2021-06-04
Container: AGILE: GIScience Series
Publisher: Copernicus GmbH
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.5194/agile-giss-2-2-2021,
  title = {H-TFIDF: What makes areas specific over time in the massive flow of tweets related to the covid pandemic?},
  author = {Rémy Decoupes and Rodrique Kafando and Mathieu Roche and Maguelonne Teisseire},
  year = {2021},
  journal = {AGILE: GIScience Series},
  doi = {10.5194/agile-giss-2-2-2021},
  url = {https://doi.org/10.5194/agile-giss-2-2-2021}
}

RIS

TY  - JOUR
TI  - H-TFIDF: What makes areas specific over time in the massive flow of tweets related to the covid pandemic?
AU  - Rémy Decoupes
AU  - Rodrique Kafando
AU  - Mathieu Roche
AU  - Maguelonne Teisseire
PY  - 2021
JO  - AGILE: GIScience Series
DO  - 10.5194/agile-giss-2-2-2021
UR  - https://doi.org/10.5194/agile-giss-2-2-2021
ER  -

APA

Decoupes, R., Kafando, R., Roche, M., & Teisseire, M. (2021). H-TFIDF: What makes areas specific over time in the massive flow of tweets related to the covid pandemic?. AGILE: GIScience Series. https://doi.org/10.5194/agile-giss-2-2-2021

Source records

crossref · retrieved 2026-09-26T05:15:59.321Z