Learning from information crises: Exploring aggregated trustworthiness in big data production

Abstract

In a crisis situation when traditional venues for information dissemination aren't reliable and information is needed immediately "aggregated trustworthiness", data verification through network evaluation and social validation, becomes an important alternative. However, the risk with evaluating credibility through trust and network reputation is that the perspective can get biased. In these socially distributed information systems there is therefore of particularly high importance to understand how data is socially produced by whom. The purpose with the research project presented in this position paper is to explore how patters of bias in information production online can become more transparent by including tools that analyze and visualize aggregated trustworthiness. the research project consists of two interconnected parts. We will first look into a recent crisis situation, the case Red Hook after Hurricane Sandy, to see how the dissemination of information took place in the recovery work, focusing on questions of credibility and trust. Thereafter, this case study will inform the design of two collaborative tools where we investigate how social validation processes can be made more transparent