Proposing a conceptual framework: social media listening for public health behavior
Shu-Feng Tsao, Helen Chen, Samantha Meyer, Zahid A. Butt

TL;DR
This paper introduces a new theory-based framework for analyzing social media data to better understand and address health misinformation, especially during COVID-19, by integrating existing theories and adding new attributes.
Contribution
It proposes a novel conceptual framework specifically designed for social listening and misinformation studies using social media data and NLP techniques.
Findings
Framework demonstrated in Freedom Convoy social media listening
Integrates multiple health and communication theories
Can be used to analyze public discourse on social media
Abstract
Existing communications and behavioral theories have been adopted to address health misinformation. Although various theories and models have been used to investigate the COVID-19 pandemic, there is no framework specially designed for social listening or misinformation studies using social media data and natural language processing techniques. This study aimed to propose a novel yet theory-based conceptual framework for misinformation research. We collected theories and models used in COVID-19 related studies published in peer-reviewed journals. The theories and models ranged from health behaviors, communications, to misinformation. They are analyzed and critiqued for their components, followed by proposing a conceptual framework with a demonstration. We reviewed Health Belief Model, Theory of Planned Behavior/Reasoned Action, Communication for Behavioral Impact, Transtheoretical Model,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMisinformation and Its Impacts · Hate Speech and Cyberbullying Detection · Social Media and Politics
MethodsAttention Is All You Need · Softmax · RAdam · Graph Self-Attention · Hyperboloid Embeddings
