Establishing Trust in Crowdsourced Data
By: Iffat Gheyas , Muhammad Rizwan Asghar , Steve Schneider and more
Potential Business Impact:
Makes online information more trustworthy and fair.
Crowdsourced data supports real-time decision-making but faces challenges like misinformation, errors, and contributor power concentration. This study systematically examines trust management practices across platforms categorised as Volunteered Geographic Information, Wiki Ecosystems, Social Media, Mobile Crowdsensing, and Specialised Review and Environmental Crowdsourcing. Identified strengths include automated moderation and community validation, while limitations involve rapid data influx, niche oversight gaps, opaque trust metrics, and elite dominance. Proposed solutions incorporate advanced AI tools, transparent reputation metrics, decentralised moderation, structured community engagement, and a ``soft power'' strategy, aiming to equitably distribute decision-making authority and enhance overall data reliability.
Similar Papers
Leveraging the Power of AI and Social Interactions to Restore Trust in Public Polls
Social and Information Networks
Find fake answers in online polls using social connections.
In Crowd Veritas: Leveraging Human Intelligence To Fight Misinformation
Information Retrieval
Helps computers spot fake news from people's opinions.
Trust and Reputation in Data Sharing: A Survey
Social and Information Networks
Makes sharing data safer for AI.