Published on in Vol 24, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37623, first published .
Understanding How and by Whom COVID-19 Misinformation is Spread on Social Media: Coding and Network Analyses

Understanding How and by Whom COVID-19 Misinformation is Spread on Social Media: Coding and Network Analyses

Understanding How and by Whom COVID-19 Misinformation is Spread on Social Media: Coding and Network Analyses

Journals

  1. Luo H, Meng X, Zhao Y, Cai M. Exploring the impact of sentiment on multi-dimensional information dissemination using COVID-19 data in China. Computers in Human Behavior 2023;144:107733 View
  2. Alexander P, Aslakson R, Barreto E, Lee J, Meissen H, Morrow B, Nazer L, Branson R, Mayer K, Napolitano N, Lane-Fall M, Sikora A, John P, Dellinger R, Parker M, Argent A, Boateng A, Green T, Kudchadkar S, Maslove D, Rech M, Sorce L, Tasker R, Buchman T, Checchia P. The Reviewer Academy of the Society of Critical Care Medicine: Key Principles and Strategic Plan. Critical Care Medicine 2023;51(9):1111 View
  3. Luo H, Meng X, Zhao Y, Cai M. Rise of social bots: The impact of social bots on public opinion dynamics in public health emergencies from an information ecology perspective. Telematics and Informatics 2023;85:102051 View
  4. Meng X, Dai C, Zhao Y, Zhou Y. Depth, breadth and structural virality: the influence of emotion, topic, authority and richness on misinformation spread. Library Hi Tech 2023 View

Books/Policy Documents

  1. Pálsdóttir Á. Human Aspects of IT for the Aged Population. View
  2. Selvakumar R, Babu V. Social Capital in the Age of Online Networking. View