Datavoidant: An AI System for Addressing Political Data Voids on Social Media
Claudia Flores-Saviaga, Shangbin Feng, Saiph Savage

TL;DR
Datavoidant is an AI-powered system designed to help independent journalists identify and address political data voids on social media, thereby combating disinformation in underrepresented communities.
Contribution
The paper introduces Datavoidant, a novel collaborative AI system that leverages machine learning to assist journalists in understanding and filling political data voids.
Findings
Journalists found Datavoidant helped them understand information ecosystems more quickly.
Users felt more confident in creating content to cover data voids.
The system facilitated collaboration among journalists to prevent disinformation.
Abstract
The limited information (data voids) on political topics relevant to underrepresented communities has facilitated the spread of disinformation. Independent journalists who combat disinformation in underrepresented communities have reported feeling overwhelmed because they lack the tools necessary to make sense of the information they monitor and address the data voids. In this paper, we present a system to identify and address political data voids within underrepresented communities. Armed with an interview study, indicating that the independent news media has the potential to address them, we designed an intelligent collaborative system, called Datavoidant. Datavoidant uses state-of-the-art machine learning models and introduces a novel design space to provide independent journalists with a collective understanding of data voids to facilitate generating content to cover the voids. We…
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Taxonomy
TopicsMisinformation and Its Impacts · Mobile Crowdsensing and Crowdsourcing · Social Media and Politics
