Deep Learning-Based Prediction of Daily Covid-19 Cases Using X (Twitter) Data

Deep Learning-Based Prediction of Daily Covid-19 Cases Using X (Twitter) Data Publisher Pubmed

Ahmed N¹ ; Saeed K¹ ; Rodrigues JL¹ ; Naeem M¹ ; Correa A¹ ; Sanabboon C¹ ; Rostam Niakan Kalhori S^{2, 3} ; Deserno TM²

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1. Information Systems and Machine Learning Lab, Department of Mathematics, Natural Science, Economics and Computer Science, Institute of Computer Science, University of Hildesheim, Germany
2. Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig, Hannover Medical School, Braunschweig, Germany
3. Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran

Source: Studies in Health Technology and Informatics Published:2024

Abstract

Due to the importance of COVID-19 control, innovative methods for predicting cases using social network data are increasingly under attention. This study aims to predict confirmed COVID-19 cases using X (Twitter) social network data (tweets) and deep learning methods. We prepare data extracted from tweets by natural language processing (NLP) and consider the daily G-value (growth rate) as the target variable of COVID-19, collected from the worldometer. We develop and evaluate a time series mixer (TSMixer) predictive model for multivariate time series. The mean squared error (MSE) loss on the test dataset was 0.0063 for 24-month Gvalue prediction when using the MinMax normalization with recursive feature elimination (RFE) and average or min aggregation method. Our findings illuminate the potential of integrating social media data to enhance daily COVID-19 case predictions and are applicable also for epidemiological forecasting purposes. © 2024 The Authors.

Style	Citing Format
MLA	Ahmed N, et al.. "Deep Learning-Based Prediction of Daily Covid-19 Cases Using X (Twitter) Data." Studies in Health Technology and Informatics, vol. 316, no. , 2024, pp. 1989-1993.
APA	Ahmed N, Saeed K, Rodrigues JL, Naeem M, Correa A, Sanabboon C, Rostam Niakan Kalhori S, Deserno TM (2024). Deep Learning-Based Prediction of Daily Covid-19 Cases Using X (Twitter) Data. Studies in Health Technology and Informatics, 316(), 1989-1993.
Chicago	Ahmed N, Saeed K, Rodrigues JL, Naeem M, Correa A, Sanabboon C, Rostam Niakan Kalhori S, Deserno TM. "Deep Learning-Based Prediction of Daily Covid-19 Cases Using X (Twitter) Data." Studies in Health Technology and Informatics 316, no. (2024): 1989-1993.
Harvard	Ahmed N et al. (2024) 'Deep Learning-Based Prediction of Daily Covid-19 Cases Using X (Twitter) Data', Studies in Health Technology and Informatics, 316(), pp. 1989-1993.
Vancouver	Ahmed N, Saeed K, Rodrigues JL, Naeem M, Correa A, Sanabboon C, et al.. Deep Learning-Based Prediction of Daily Covid-19 Cases Using X (Twitter) Data. Studies in Health Technology and Informatics. 2024;316():1989-1993.
BibTex	@article{ author = {Ahmed N and Saeed K and Rodrigues JL and Naeem M and Correa A and Sanabboon C and Rostam Niakan Kalhori S and Deserno TM}, title = {Deep Learning-Based Prediction of Daily Covid-19 Cases Using X (Twitter) Data}, journal = {Studies in Health Technology and Informatics}, volume = {316}, number = {}, pages = {1989-1993}, year = {2024} }
RIS	TY - JOUR AU - Ahmed N AU - Saeed K AU - Rodrigues JL AU - Naeem M AU - Correa A AU - Sanabboon C AU - Rostam Niakan Kalhori S AU - Deserno TM TI - Deep Learning-Based Prediction of Daily Covid-19 Cases Using X (Twitter) Data JO - Studies in Health Technology and Informatics VL - 316 IS - SP - 1989 EP - 1993 PY - 2024 ER -

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