Using Google Trends, Gaussian Mixture Models and DBSCAN for the estimation of Twitter user home location
In this work we propose a novel approach to estimate the home location of Twitter users. Given a list of Twitter users, we extract their timelines (up to 3,200) using the Twitter Application Programming Interface (API) service. We use Google Trends to obtain a list of cities in which the nouns of a...
| Autor principal: | |
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| Outros Autores: | , |
| Formato: | conferencePaper |
| Idioma: | eng |
| Publicado em: |
2020
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/1822/68509 |
| País: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/68509 |