LocBERT: Improving Social Media User Location Prediction Using Fine-Tuned BERT
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-39689-2_3
Reference21 articles.
1. “Global Social Media Statistics — DataReportal – Global Digital Insights.” https://datareportal.com/social-media-users. Accessed 26 Feb 2023
2. Santos, J.S., Bernardini, F., Paes, A.: A survey on the use of data and opinion mining in social media to political electoral outcomes prediction. Soc. Netw. Anal. Min. 11(1), 1–39 (2021). https://doi.org/10.1007/s13278-021-00813-4
3. Khan, A., et al.: Predicting politician’s supporters’ network on twitter using social network analysis and semantic analysis. Sci. Program. 2020, 1–17 (2020). https://doi.org/10.1155/2020/9353120
4. Chauhan, P., Sharma, N., Sikka, G.: The emergence of social media data and sentiment analysis in election prediction. J. Ambient. Intell. Humaniz. Comput. 12(2), 2601–2627 (2020). https://doi.org/10.1007/s12652-020-02423-y
5. Khan, A., et al.: Election prediction on twitter: a systematic mapping study. Complexity 2021, 1–27 (2021). https://doi.org/10.1155/2021/5565434
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