A Google trends spatial clustering approach for a worldwide Twitter user geolocation
User location data is valuable for diverse social media analytics. In this paper, we address the non-trivial task of estimating a worldwide city-level Twitter user location considering only historical tweets. We propose a purely unsupervised approach that is based on a synthetic geographic sampling...
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| Other Authors: | , |
| Format: | article |
| Language: | eng |
| Published: |
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1822/66815 |
| Country: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/66815 |