Big Data for Social Media Analysis During the COVID-19 Pandemic: An Emotion Analysis Based on Influences from Social Networks-Reference-Cited by-同舟云学术

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Big Data for Social Media Analysis During the COVID-19 Pandemic: An Emotion Analysis Based on Influences from Social Networks

Published:2023 Issue: Volume: Page:121-139
ISSN:2731-6483
Container-title:Big Data Analytics for Smart Transport and Healthcare Systems
language:
Short-container-title:

Author:

Pourroostaei Ardakani Saeid^ORCID,Cheshmehzangi Ali^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-6620-2_7

Reference38 articles.

1. Ahmed, Mohammed Emtiaz, Md Rafiqul Islam Rabin, and Farah Naz Chowdhury. 2020. Covid-19: Social media sentiment analysis on reopening. arXiv preprint arXiv:2006.00804.

2. Ardakani, Saeid Pourroostaei, Can Zhou, Xuting Wu, Yingrui Ma, and Jizhou Che. 2021. A data-driven affective text classification analysis. In 20th IEEE international conference on machine learning and applications (ICMLA), virtual conference.

3. Breiman, Leo. 2023. Random forests. https://www.stat.berkeley.edu/~breiman/randomforest2001.pdf. Retrieved February 2023.

4. C3Ai. 2023. Mean absolute error. https://c3.ai/glossary/data-science/mean-absolute-error/. Retrieved February 2023.

5. C3Ai. 2023. Root mean square error. https://c3.ai/glossary/data-science/root-mean-square-error-rmse/. Retrieved February 2023.

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