# Characterization of Misinformation Dynamics in COVID-19 related health information in online social media

> **NIH NIH R01** · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · 2020 · $63,106

## Abstract

Abstract:
Social media has become predominant as a source of information for many health care consumers. However
false and misleading information are a pervasive problem in this context. Specifically, during CVID-19 pandemic,
misinformation has been a significant public health challenge, impeding the effectiveness of public health
awareness campaigns and resulting in suboptimal responsiveness to the communication of legitimate risk-
related information. In the proposed research, we will apply our “Pragmatics to Reveal Intent in Social Media
(PRISM) framework to facilitate automated detection of intent and belief attributes underlying COVID-19 related
misinformation. The PRISM framework aims to incorporate and integrate communication intent, semantics and
structure of online communication to study social processes and cognitive factors underlying misinformation
comprehension. Such analysis forms the foundational step towards characterization of misinformation seeding
and perception in digital social settings, ultimately allowing us to develop scalable and reliable computational
infrastructure that can help formulate resilient and effective dissemination approaches to negotiate
misinformation spread, easing public health burden and informing policy regulations as needed.

## Key facts

- **NIH application ID:** 10176817
- **Project number:** 3R01LM012974-02S1
- **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
- **Principal Investigator:** SAHITI MYNENI
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $63,106
- **Award type:** 3
- **Project period:** 2020-07-01 → 2021-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10176817

## Citation

> US National Institutes of Health, RePORTER application 10176817, Characterization of Misinformation Dynamics in COVID-19 related health information in online social media (3R01LM012974-02S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10176817. Licensed CC0.

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