Tweeting for Health Using Real-time Mining and Artificial Intelligence-Based Analytics: Design and Development of a Big Data Ecosystem for Detecting and Analyzing Misinformation on Twitter.

ABSTRACT:

Background

Digital misinformation, primarily on social media, has led to harmful and costly beliefs in the general population. Notably, these beliefs have resulted in public health crises to the detriment of governments worldwide and their citizens. However, public health officials need access to a comprehensive system capable of mining and analyzing large volumes of social media data in real time.

Objective

This study aimed to design and develop a big data pipeline and ecosystem (UbiLab Misinformation Analysis System [U-MAS]) to identify and analyze false or misleading information disseminated via social media on a certain topic or set of related topics.

Methods

U-MAS is a platform-independent ecosystem developed in Python that leverages the Twitter V2 application pr

SUBMITTER: Morita PP 

PROVIDER: S-EPMC10337356 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature