A content analysis of social media on outbreak of infodemic amidst COVID‑19 pandemic
Volume 11, Issue 9, October 2021, Pages 1-5
. Anusha Divvi, . Shivashankar Kengadaran, . Lakshmi Subhashini Katuri, . M. Kavitha, . Arunkumar Sundaragopal, . Vani Anusha, . Sivabalakumaran Kengadaran, . Hemachandran Sekar
Abstract BACKGROUND: With so much content on social media platforms about COVID‑19, determining
which information is reliable can be a daunting task. Hence, this study is aimed to analyze various
posts with regard to COVID‑19 on various social media platforms for their reliability and also examined
various factors that influence information reliability.
MATERIALS AND METHODS: A cross‑sectional study was conducted, with 934 samples related
to coronavirus pandemic published on Twitter, Instagram, and Facebook using systematic random
sampling. We adopted the criteria given by Paul Bradshaw and modified to assess the characteristics
of the samples. Training and calibration of the investigators were carried out for 3 consecutive days
before beginning the study. The data were analyzed using the Chi‑square test and multinomial logistic
regression to estimate the odds ratios.
RESULTS: Out of 934 samples studied, only 570 (61%) were found to be reliable of which
243 (42.6%) were from Twitter, 117 (20.6%) from Instagram, and 210 (36.8%) from Facebook.
We found that the reliability of the information on social media platforms is significantly influenced
by network (odds: 1.32; 95% confidence interval [CI]: 1.16–1.52; P = 0.036), content (odds: 1.83;
95% CI: 1.69–1.92; P = 0.009), contextual update (odds: 1.41; 95% CI: 1.24–1.53) and age of the
account (odds: 1.92; 95% CI: 1.64–2.09; P = 0.002).
CONCLUSION: Our study shows that the reliability of the social media posts significantly depends
on the network, contextual update, and age of the account. Hence, cross verifying the information
from a reliable source is the need of the hour to prevent panic and mental distress.
