Improved Classification of Crisis-Related Data on Twitter using Contextual Representations-Reference-Cited by-同舟云学术

Improved Classification of Crisis-Related Data on Twitter using Contextual Representations

Published:2020 Issue: Volume:167 Page:962-968
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Madichetty Sreenivasulu,M Sridevi

Publisher

Elsevier BV

Subject

General Engineering

Reference26 articles.

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3. Madisetty, S., Desarkar, M.S., (2017)a. An ensemble based method for predicting emotion intensity of tweets, in: International Conference on Mining Intelligence and Knowledge Exploration, Springer. pp. 359–370.

4. Gupta, H., Jamal, M.S., Madisetty, S., Desarkar, M.S., (2018). A framework for real-time spam detection in twitter, in: 2018 10th International Conference on Communication Systems & Networks (COMSNETS), IEEE. pp. 380–383.

5. Barnwal, D., Ghelani, S., Krishna, R., Basu, M., Ghosh, S., (2019). Identifying fact-checkable microblogs during disasters: a classification-ranking approach, in: Proceedings of the 20th International Conference on Distributed Computing and Networking, ACM. pp. 389–392.

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