TSViz: a data stream architecture to online collect, analyze, and visualize tweets (2017)
- Authors:
- Autor USP: MELLO, RODRIGO FERNANDES DE - ICMC
- Unidade: ICMC
- DOI: 10.1145/3019612.3019811
- Subjects: BANCO DE DADOS; RECONHECIMENTO DE PADRÕES; MÍDIAS SOCIAIS; SISTEMAS DINÂMICOS
- Keywords: Twitter monitoring; data streams; big data
- Language: Inglês
- Imprenta:
- Source:
- Título: Proceedings
- Conference titles: Symposium on Applied Computing - SAC
- Status:
- Nenhuma versão em acesso aberto identificada
-
ABNT
RIOS, Ricardo A et al. TSViz: a data stream architecture to online collect, analyze, and visualize tweets. 2017, Anais.. New York: ACM, 2017. Disponível em: https://doi.org/10.1145/3019612.3019811. Acesso em: 09 abr. 2026. -
APA
Rios, R. A., Pagliosa, P. A., Ishii, R. P., & Mello, R. F. de. (2017). TSViz: a data stream architecture to online collect, analyze, and visualize tweets. In Proceedings. New York: ACM. doi:10.1145/3019612.3019811 -
NLM
Rios RA, Pagliosa PA, Ishii RP, Mello RF de. TSViz: a data stream architecture to online collect, analyze, and visualize tweets [Internet]. Proceedings. 2017 ;[citado 2026 abr. 09 ] Available from: https://doi.org/10.1145/3019612.3019811 -
Vancouver
Rios RA, Pagliosa PA, Ishii RP, Mello RF de. TSViz: a data stream architecture to online collect, analyze, and visualize tweets [Internet]. Proceedings. 2017 ;[citado 2026 abr. 09 ] Available from: https://doi.org/10.1145/3019612.3019811 - A novel approach to quantify novelty levels applied on ubiquitous music distribution
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