Dramatic Increases in Telehealth-Related Tweets during the Early COVID-19 Pandemic: A Sentiment Analysis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Raw Data
2.2. Manual Data Annotation
2.3. Automatic NLP-Based Annotation
3. Results
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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BERT Model | Accuracy | Precision | Recall | F1 | AUROC * | |
---|---|---|---|---|---|---|
Telehealth | BERT-base | 98.3% | 98.5% | 99.7% | 99.1 | 0.982 |
BERT-telehealth | 98.5% | 98.8% | 99.5% | 99.2 | 0.989 | |
Sentiment | BERT-base | 67.8% | 63.6% | 56.3% | 58.8 | N/A |
BERT-telehealth | 70.4% | 70.0% | 61.7% | 64.5 | N/A | |
User | BERT-base | 67.5% | 53.8% | 53.7% | 53.7 | N/A |
BERT-telehealth | 69.0% | 57.6% | 54.7% | 56.0 | N/A | |
COVID-19 | BERT-base | 93.6% | 91.3% | 83.2% | 87.1 | 0.940 |
BERT-telehealth | 94.9% | 94.5% | 85.2% | 89.6 | 0.952 |
Category | Definition | User Count | (%) |
---|---|---|---|
Clinician | A person who treats patients | 15,136 | (7.9) |
Consumer | A patient or other user of telehealth | 6381 | (3.3) |
Policymaker | A person who makes or influences governmental policy | 1544 | (0.8) |
Vendor | Any user with an economic interest in telehealth | 24,888 | (12.9) |
Other | Any other user who cannot be classified as above | 144,481 | (75.1) |
Category | Definition | Example Tweet | n | (%) |
---|---|---|---|---|
Positive | Supports use of telehealth | Telehealth may be especially helpful as an initial option for COVID-19 | 112,721 | (58.6) |
Neutral | No overt positive or negative sentiment | Telehealth During COVID-19: New Rules and Considerations | 72,369 | (37.6) |
Negative | Dissatisfaction with telehealth | I have a telehealth appointment with my tomorrow and it’s going to be so weird | 7340 | (3.8) |
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Champagne-Langabeer, T.; Swank, M.W.; Manas, S.; Si, Y.; Roberts, K. Dramatic Increases in Telehealth-Related Tweets during the Early COVID-19 Pandemic: A Sentiment Analysis. Healthcare 2021, 9, 634. https://doi.org/10.3390/healthcare9060634
Champagne-Langabeer T, Swank MW, Manas S, Si Y, Roberts K. Dramatic Increases in Telehealth-Related Tweets during the Early COVID-19 Pandemic: A Sentiment Analysis. Healthcare. 2021; 9(6):634. https://doi.org/10.3390/healthcare9060634
Chicago/Turabian StyleChampagne-Langabeer, Tiffany, Michael W. Swank, Shruthi Manas, Yuqi Si, and Kirk Roberts. 2021. "Dramatic Increases in Telehealth-Related Tweets during the Early COVID-19 Pandemic: A Sentiment Analysis" Healthcare 9, no. 6: 634. https://doi.org/10.3390/healthcare9060634
APA StyleChampagne-Langabeer, T., Swank, M. W., Manas, S., Si, Y., & Roberts, K. (2021). Dramatic Increases in Telehealth-Related Tweets during the Early COVID-19 Pandemic: A Sentiment Analysis. Healthcare, 9(6), 634. https://doi.org/10.3390/healthcare9060634