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Springer Nature Switzerland
Reference48 articles.
1. Cheng, Z., Caverlee, J., Lee, K.: You are where you tweet: a content-based approach to geo-locating twitter users. In: Proceedings of the 19th ACM international conference on Information and knowledge management, pp. 759–768 (2010)
2. Chi, L., Lim, K.H., Alam, N., Butler, C.J.: Geolocation prediction in twitter using location indicative words and textual features. In: Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT), pp. 227–234 (2016)
3. Chong, W.H., Lim, E.P.: Exploiting contextual information for fine-grained tweet geolocation. In: Proceedings of the International AAAI Conference on Web and Social Media, vol. 11 (2017)
4. Chong, W.H., Lim, E.P.: Exploiting user and venue characteristics for fine-grained tweet geolocation. ACM Trans. Inf. Syst. (TOIS) 36(3), 1–34 (2018)
5. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: Pre-training of deep bidirectional transformers for language understanding. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 4171–4186. Association for Computational Linguistics, Minneapolis, Minnesota (2019). https://doi.org/10.18653/v1/N19-1423. https://aclanthology.org/N19-1423
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