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Natural Language Processing–Powered Real-Time Monitoring Solution for Vaccine Sentiments and Hesitancy on Social Media: System Development and Validation

Natural Language Processing–Powered Real-Time Monitoring Solution for Vaccine Sentiments and Hesitancy on Social Media: System Development and Validation

Neutral: posts that are related to vaccines or vaccination topics but contain no sentiment, the sentiment is unclear, or they contain both negative and positive sentiments. Example: “The following report is specifically for the MMR vaccine, but you can browse around for others” Example: “I just learned that there are more than 50 strains of HPV...I always thought the vaccine prevented all strains.”

Liang-Chin Huang, Amanda L Eiden, Long He, Augustine Annan, Siwei Wang, Jingqi Wang, Frank J Manion, Xiaoyan Wang, Jingcheng Du, Lixia Yao

JMIR Med Inform 2024;12:e57164

Perspectives and Experiences of Patients With Thyroid Cancer at a Global Level: Retrospective Descriptive Study of Twitter Data

Perspectives and Experiences of Patients With Thyroid Cancer at a Global Level: Retrospective Descriptive Study of Twitter Data

Through this analysis, we aim to examine the content and sentiments expressed in these tweets on a global scale. We searched Twitter for tweets posted between January 1 and December 31, 2020, that included tweets containing the term “thyroid cancer” and collected the data using the Twitter scraping tool Twint.

Sununtha Meksawasdichai, Tassanee Lerksuthirat, Boonsong Ongphiphadhanakul, Chutintorn Sriphrapradang

JMIR Cancer 2023;9:e48786

Understanding Concerns, Sentiments, and Disparities Among Population Groups During the COVID-19 Pandemic Via Twitter Data Mining: Large-scale Cross-sectional Study

Understanding Concerns, Sentiments, and Disparities Among Population Groups During the COVID-19 Pandemic Via Twitter Data Mining: Large-scale Cross-sectional Study

Such widely penetrating and long-lasting impacts are likely to cause disproportionate burdens on different population groups, incurring varied concerns and sentiments among them. Therefore, it is of great importance to understand the disparities in the responses of these population groups to COVID-19 for better informed public health research and intervention.

Chunyan Zhang, Songhua Xu, Zongfang Li, Shunxu Hu

J Med Internet Res 2021;23(3):e26482