An improved machine learning technique for identify informative COVID-19 tweets

Author:

Malla SreejagadeeshORCID,Alphonse P. J. A.

Publisher

Springer Science and Business Media LLC

Subject

Strategy and Management,Safety, Risk, Reliability and Quality

Reference34 articles.

1. Agarwal A, Xie B, Vovsha I, Rambow O, Passonneau RJ (2011) Sentiment analysis of twitter data. In: Proceedings of the workshop on language in social media (LSM 2011), pp. 30–38

2. Aggarwal CC, Zhai C (2012) A survey of text classification algorithms. Mining text data. Springer, Boston, pp 163–222

3. Babu YP, Eswari R (2020) CIA_NITT at WNUT-2020 Task 2: classification of COVID-19 tweets using pre-trained language models. arXiv preprint arXiv:2009.05782, pp. 471–474

4. Bethard S, Carpuat M, Cer D, Jurgens D, Nakov P, Zesch T (2016) Proceedings of the 10th International workshop on semantic evaluation (SemEval-2016). In: Proceedings of the 10th international workshop on semantic evaluation (SemEval-2016), pp. 1–46

5. Bharti SK, Babu KS, Jena SK (2015) Parsing-based sarcasm sentiment recognition in twitter data. In: 2015 IEEE/ACM International conference on advances in social networks analysis and mining (ASONAM), pp. 1373–1380

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