Academic Journal

Sentiment Analysis of Twitter Posts Related to a COVID-19 Test & Trace Program in NYC.

التفاصيل البيبلوغرافية
العنوان: Sentiment Analysis of Twitter Posts Related to a COVID-19 Test & Trace Program in NYC.
المؤلفون: Tsai, Krystle A., Chau, Michelle M., Wang, Juncheng, Thorpe, Lorna E., Massar, Rachel E., Conderino, Sarah, Berry, Carolyn A., Islam, Nadia S., Bershteyn, Anna, Bragg, Marie A.
المصدر: Journal of Urban Health; Oct2024, Vol. 101 Issue 5, p898-901, 4p
مصطلحات موضوعية: SOCIAL media, SENTIMENT analysis, GOVERNMENT agencies, COVID-19 testing
مستخلص: As part of a program evaluation of the New York City Test & Trace program (T2)—one of the largest such programs in the USA—we conducted a study to assess how implementing organizations (NYC Health + Hospitals, government agencies, CBOs) communicated information about the T2 program on Twitter. Study aims were as follows: (1) quantify user engagement of posts ("tweets") about T2 by NYC organizations on Twitter and (2) examine the emotional tone of social media users' T2-related tweets in our sample of 1987 T2-related tweets. Celebrities and CBOs generated more user engagement (0.26% and 0.07%, respectively) compared to government agencies (e.g., Mayor's Office, 0.0019%), reinforcing the value of collaborating with celebrities and CBOs in social media public health campaigns. Sentiment analysis revealed that positive tweets (46.5%) had higher user engagement than negative tweets (number of likes: R2 =.095, p <.01), underscoring the importance of positively framing messages for effective public health campaigns. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Urban Health is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
قاعدة البيانات: Complementary Index
الوصف
تدمد:10993460
DOI:10.1007/s11524-024-00906-3