Cargando…
Mining association rules from COVID-19 related twitter data to discover word patterns, topics and inferences
This work utilizes data from Twitter to mine association rules and extract knowledge about public attitudes regarding worldwide crises. It exploits the COVID-19 pandemic as a use case, and analyzes tweets gathered between February and August 2020. The proposed methodology comprises topic extraction...
Autores principales: | Koukaras, Paraskevas, Tjortjis, Christos, Rousidis, Dimitrios |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758561/ https://www.ncbi.nlm.nih.gov/pubmed/36569358 http://dx.doi.org/10.1016/j.is.2022.102054 |
Ejemplares similares
-
Using Twitter to Predict Chart Position for Songs
por: Tsiara, Eleana, et al.
Publicado: (2020) -
Discovering protein–DNA binding sequence patterns using association rule mining
por: Leung, Kwong-Sak, et al.
Publicado: (2010) -
Discovering symptom patterns of COVID-19 patients using association rule mining
por: Tandan, Meera, et al.
Publicado: (2021) -
An Association Rule Mining Approach to Discover lncRNAs Expression Patterns in Cancer Datasets
por: Cremaschi, Paolo, et al.
Publicado: (2015) -
Discovering spatial interaction patterns of near repeat crime by spatial association rules mining
por: He, Zhanjun, et al.
Publicado: (2020)