Sentiment analysis of COVID-19 social media data through machine learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-022-13492-w.pdf
Reference51 articles.
1. Ansari GJ, Shah JH, Yasmin M, Sharif M, Fernandes SL (2018) A novel machine learning approach for scene text extraction. Futur Gener Comput Syst 87:328–340
2. Basha SM, Rajput DS (2017) Evaluating the impact of feature selection on overall performance of sentiment analysis. In: Proceedings of the 2017 international conference on information technology. pp. 96-102
3. Basha SM, Rajput DS (2018) Parsing based sarcasm detection from literal language in tweets. Recent Pat Comput Sci 11(1):62–69
4. Basha SM, Rajput DS (2018) A supervised aspect level sentiment model to predict overall sentiment on tweeter documents. Int J Metadata Semant Ontol 13(1):33–41
5. Basha SM, Rajput DS (2019) An innovative topic-based customer complaints sentiment classification system. Int J Bus Innov Res 20(3):375–391
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