Active Learning for Identifying Disaster-Related Tweets: A Comparison with Keyword Filtering and Generic Fine-Tuning

Author:

Hanny David,Schmidt Sebastian,Resch Bernd

Publisher

Springer Nature Switzerland

Reference58 articles.

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3. Ahmed, L., Ahmad, K., Said, N., Qolomany, B., Qadir, J., Al-Fuqaha, A.: Active learning based Federated learning for waste and natural disaster image classification. IEEE Access 8, 208518–208531 (2020)

4. Barbieri, F., Anke, L.E., Camacho-Collados, J.: XLM-T: multilingual language models in Twitter for sentiment analysis and beyond. In: Proceedings of the Thirteenth Language Resources and Evaluation Conference, Marseille, France, 2022, pp. 258–266. European Language Resources Association

5. Berners-Lee, T.: Web architecture: filtering and censorship. https://www.w3.org/DesignIssues/Filtering.html (1997)

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