Selected article for: "day report and large scale"

Author: Tan, E. Y.; Wee, R. R.; Saw, Y. E.; Heng, K. J.; Chin, J. W.; Tong, E. M.; Liu, J. C.
Title: Tracking WhatsApp behaviors during a crisis: A longitudinal observation of messaging activities during the COVID-19 pandemic
  • Cord-id: 8270zc0a
  • Document date: 2020_9_29
  • ID: 8270zc0a
    Snippet: During a crisis, the messaging platform WhatsApp allows crisis-related information to be disseminated quickly. Although case studies have documented how WhatsApp has shaped crisis outcomes in both beneficial and harmful ways, little is known about: (i) how crisis-related content is spread; (ii) characteristics of users based on usage patterns; or (iii) how usage patterns link to well-being. During the coronavirus disease 2019 (COVID-19) crisis, this study used the experience sampling method to t
    Document: During a crisis, the messaging platform WhatsApp allows crisis-related information to be disseminated quickly. Although case studies have documented how WhatsApp has shaped crisis outcomes in both beneficial and harmful ways, little is known about: (i) how crisis-related content is spread; (ii) characteristics of users based on usage patterns; or (iii) how usage patterns link to well-being. During the coronavirus disease 2019 (COVID-19) crisis, this study used the experience sampling method to track the daily WhatsApp usage of 151 adults throughout one week (capturing a total of 924 days of crisis-related communication). Each day, participants reported the extent to which they had received, forwarded, or discussed COVID-19- related content. During the week-long monitoring, most participants (94.7%) reported at least one COVID-19 related use of WhatsApp. Those who engaged with more COVID-19 content in personal chats were more likely to report having COVID-19 thoughts throughout the day. We further observed that around 1 in 10 individuals (14%) were chronic users who received and shared forwarded COVID-19 messages at a high volume; this group may represent everyday "super spreaders" of crisis-related content. Together, these findings provide an empirical base for policy makers to manage risk communication during large-scale crises.

    Search related documents:
    Co phrase search for related documents
    • accuracy verify and machine learning: 1
    • activity engage and longitudinal design: 1
    • activity total and machine learning: 1
    • address able and machine learning: 1
    • address important and machine learning: 1, 2, 3, 4, 5
    • longitudinal design and low confidence: 1
    • longitudinal design and machine learning: 1, 2, 3, 4, 5
    • low confidence and machine learning: 1, 2, 3, 4